This study explores the impact of two planetary boundary layer (PBL) parameterisations on simulated concentrations of four main air pollutants (ozone, nitrogen dioxide [NO2], and particulate matter [PM] with diameters of < 10 and < 2.5 µm), and evaluates their results against radiosonde measurements in Europe. The two PBL parameterisations used are (i) based on the bulk Richardson number approach under stable conditions and the Brunt-Väisälä frequency under neutral and stable conditions, and (ii) based on turbulent kinetic energy. The regional chemical transport model MATCH was applied on a region of Western Europe. MATCH was forced by meteorological data from the HARMONIE–AROME numerical weather prediction model, using the same setup as in the ACCORD consortium. The horizontal resolution was 2.5 km × 2.5 km, over 65 vertical levels grouped in pairs in the MATCH model. The time frame for this study was during a heat wave in July 2022. The CAMS regional emissions were interpolated into the MATCH simulation grid. The preliminary results show that the MATCH model is overestimating the PBL height at noon, independently of the method used to calculate it in the model. Results are not conclusive for comparisons with observations at midnight. The impact on air quality predictions is mostly seen for ozone during the night, and on PM and NO2 during the first hours in the morning.

The Copernicus Atmosphere Monitoring Service (CAMS) delivers a wide range of free and open products in relation to atmospheric composition at global and regional scales. The CAMS Regional Service produces daily forecasts, analyses, and reanalyses of air quality in Europe. This service relies on a distributed modelling production by 11 teams in 10 European countries: CHIMERE (France), DEHM (Denmark), EMEP (Norway), EURAD-IM (Germany), GEM-AQ (Poland), LOTOS-EUROS (the Netherlands), MATCH (Sweden), MINNI (Italy), MOCAGE (France), MONARCH (Spain), and SILAM (Finland). The project management and coordination of the service is conducted by a Centralised Regional Production Unit. Every day, each model produces 24 h analyses for the previous day and 97 h forecasts for 19 chemical species over a spatial domain at 0.1 x 0.1 degrees resolution (approximately 10 km x 10 km), with 420 points in latitude and 700 in longitude and 10 vertical levels. Six pollen species are also delivered for the surface forecasts. The 11 individual models are then combined into an ENSEMBLE median. In total, more than 82 billion data points are made available for public use on a daily basis.The design of the system follows clear technical requirements in terms of consistency in the model setup and forcing fields (meteorology, surface anthropogenic emission fluxes, and chemical boundary conditions). But it also benefits from a diversity in the description of atmospheric processes through the design of the 11 European chemistry-transport models (CTMs) involved.The present article aims to provide a comprehensive technical documentation, both for the setup and for the diversity of CTMs involved in the service. We also include an overview of the main output products, their public dissemination, and the related evaluation and quality control strategy.

Chemical transport models (CTM) are powerful tools to assess the health risk of population exposure to atmospheric pollutants. CTM simulations can cover large areas and provide quantitative estimates of air pollution concentrations. This is especially useful in areas where surface measurements are scarce and satellite data are acquired at low frequencies (limited to almost clear skies). However, the performance of these models is strongly dependent on the available input data. As partners in the project “Arctic Community Resilience to Boreal Environmental Change: Assessing Risks from Fire and Diseases” (ACRoBEAR), we have used the MATCH CTM, developed by the Swedish Meteorological and Hydrological Institute—SMHI, to assess the risk associated with forest fire smoke plumes. The work presented focuses on model runs for Europe from June to August 2018. The model domain covered all parts of Europe with major fires during that period, and extended well beyond the Arctic Circle. Two fire emissions inventories were used—the Copernicus GFAS product, with 0.1° × 0.1° horizontal resolution, and the FINNv2.2–NCAR inventory, with a finer spatial resolution (1 km × 1 km). The impacts of wildfire-related particulate matter on the extinction coefficient and tropospheric ozone concentrations were tested with the MATCH model. The model results are sensitive to the correction of the photolysis rate with the extinction coefficient impacting the simulated near-surface ozone concentrations by up to 50 µg m-3, on an hourly basis.

Ammonia (NH3) is a central component of atmospheric reactive nitrogen, and a precursor gas that forms airborne particulate matter including nitrate and sulfate aerosol. Reducing ammonia emissions, primarily from agriculture, is a major challenge for air pollution mitigation and environmental protection. This work assesses the effects of ammonia emission reductions in Sweden, which is one of the EU Member States that are currently not meeting their emission reduction commitments. We apply the regional chemical transport model MATCH with improved NH3 treatment, and benchmark the updated model setup against surface observations of atmospheric NH3 and other nitrogen species for a large-scale model domain over Europe. We perform high-resolution regional simulations over Sweden, and compare the effects of reducing the emissions of (1) agricultural NH3, and (2) nitrogen oxides (NOx) from road transport, which is the second major nitrogen source in Sweden. The results show the potential of national NH3 emission reductions to mitigate NH3 levels, fine particulate matter (PM2.5) and nitrogen deposition within Sweden. While cutting NOx emissions is important for air pollution abatement through NOx mitigation, in Sweden the reductions have only minor or negligible effects on PM2.5 and nitrogen deposition. This demonstrates the benefits of NH3 reduction for both air quality and environment, and the impact of national abatement actions.

An accurate characterization of the temporal distribution in primary emissions is essential for air quality modeling. This study evaluates the impact of replacing the default temporal profiles in the Copernicus Atmosphere Monitoring Service (CAMS) European air quality multi-model ensemble with an updated dataset (CAMS-REG-TEMPO). The sensitivity of 11 regional models and the ensemble to these changes is assessed by comparing modeled and observed monthly, weekly, and diurnal cycles of nitrogen dioxide (NO2), ozone (O-3), coarse particulate matter (PM10), and fine particulate matter (PM2.5) across Europe. NO2 shows the greatest improvement, with weekly cycle correlations increasing up to +0.17 due to better road transport emissions representation. PM10 correlations improve in winter (up to +0.13 weekly and +0.07 diurnal) due to refined residential wood combustion emissions. PM2.5 correlations remain largely unchanged, except for diurnal cycles, which improve in winter (+0.18) but slightly degrade in spring and summer (-0.02). O-3 is the least affected, as correlations were already high with default profiles (0.9-0.95). For some species and timescales (e.g., NO2 diurnal cycles), results vary across models, highlighting the complex interactions between emission timing and atmospheric processes. CAMS-REG-TEMPO has little effect on annual RMSE and bias, aside from slight improvements in high PM10 concentrations. Overall, the findings support implementing CAMS-REG-TEMPO in the operational CAMS multi-model ensemble.

The contributions to PM2.5 from different emission sectors across central Chile and the Santiago metropolitan area during summer/fall and winter have been evaluated using a chemical transport model. The simulations generally underestimate the mean PM2.5 concentrations compared to measurements conducted at stations in Santiago that belong to the Chilean National Air Quality Information System (SINCA). The potential reasons for this discrepancy include underestimated direct PM2.5 emissions, missing emissions for semi- and intermediately volatile organic compounds (SVOCs and IVOCs) and overestimated wind speeds in the simulations. The simulated winter PM2.5 concentrations in Santiago are lower and higher than the values observed during nighttime, and daytime and late evening, respectively, which may be related to excessive simulated wind speeds, as well as to uncertainties in the diurnal variation in the emissions. During summer/fall, the simulated diurnal variation better agrees with the observations, but the peak concentrations during the morning are underestimated, whereas those during the evening are overestimated. The simulated contributions of different aerosol components to the PM2.5 at one station in Santiago are all lower than the observed values, except for elemental carbon equivalent black carbon (BCe), which exhibit comparable or higher levels in the simulations. The absolute differences are the largest for the total organic matter, whereas the relative differences are the largest for BCe and ammonium. The simulated sector contributions indicate that emissions originating from transport and construction machinery dominate the PM2.5 in Santiago; however, residential wood combustion is the primary source in other urban areas of central Chile, except near major point sources. Away from urban areas, traffic routes and major industrial sources, secondary inorganic aerosol (SIA) is estimated to be the largest component of the aerosol, whereas the simulated secondary organic aerosol (SOA) only contributes a small fraction.

Evaluation of simplifications for multi-compound nucleation provides assessments of best practices and possible biases in model representation of nanoparticle formation.

Abstract. This paper outlines the structure and usage of the GenChem system, which includes a chemical pre-processor GenChem.py) and a simple box model (boxChem). GenChem provides scripts and input files for converting chemical equations into differential form for use in atmospheric chemical transport models (CTMs) and/or the boxChem system. Although GenChem is primarily intended for users of the Meteorological Synthesizing Centre – West of the European Monitoring and Evaluation Programme (EMEP MSC-W) CTM and related systems, boxChem can be run as a stand-alone chemical solver, enabling for example easy testing of chemical mechanisms against each other. This paper presents an outline of the usage of the GenChem system, explaining input and output files, and presents some examples of usage. The code needed to run GenChem is released as open-source code under the GNU license.

Wetlands play a vital role in terrestrial carbon (C) sequestration, but the sensitivity of their C stocks to disturbance remains uncertain, requiring enhanced understanding of the processes that govern C storage and removal. The unique conditions in wetlands from different hydrogeomorphic (HGM) classes likely regulate the cycling, storage and vulnerabilities of wetland soil C stocks. To determine how differences in hydrogeomorphic setting influence soil organic carbon (SOC) processing, we compared C content and composition between depressional and slope wetlands located in the Colorado Rocky Mountains. Isolated depressional wetlands were characterized by seasonally declining water tables, slow discharge, high clay content, and thick organic horizons. Slope wetlands received perennial groundwater inputs and had coarser soil textures and thinner organic horizons. Seasonal snowmelt inputs coupled with low hydrologic discharge and higher clay content in depressional wetlands were predicted to sustain anoxic conditions, leading to high SOC content and chemically reduced C compounds. Depressional wetland soils had higher SOC content at depth and higher porewater DOC concentrations compared to slope wetland soils. Solid-state 13C nuclear magnetic resonance spectroscopy demonstrated that aliphatic compounds were the dominant SOC component in depressional wetlands compared to aromatic C forms in the slope wetlands. The higher prevalence of aliphatic carbon in depressional wetland soils suggests that stored SOC is protected by anaerobic conditions to a greater extent than in the slope wetlands, and that this SOC may be more vulnerable to drying and oxic conditions associated with wetland drainage and climate change.

The reduced representation of isoprene degradation in the Common Representative Intermediates (CRI) mechanism has been systematically updated, using the Master Chemical Mechanism (MCM v3.3.1) as a reference benchmark, with the updated mechanism being released as CRI v2.2. The complete isoprene degradation mechanism in CRI v2.2 consists of 186 reactions of 56 closed shell and free radical species, this being an order of magnitude reduction in size compared with MCM v3.3.1. The chemistry initiated by reaction with OH radicals, NO3 radicals and ozone (O3) is treated. An overview of the updates is provided, within the context of reported kinetic and mechanistic information. The revisions mainly relate to the OH-initiated chemistry, which tends to dominate under atmospheric conditions, although these include updates to the chemistry of products that are also generated from the O3- and NO3-initiated oxidation. The revisions have impacts in a number of key areas, including recycling of HOx and NOx. The performance of the CRI v2.2 isoprene mechanism has been compared with those of the preceding version (CRI v2.1) and the reference MCM v3.3.1 over a range of relevant conditions, using a box model of the tropical forested boundary layer. In addition, tests are carried out to ensure that the performance of MCM v3.3.1 remains robust to more recently reported information. CRI v2.2 has also been implemented into the STOCHEM chemistry-transport model, with a customized close-variant of CRI v2.2 implemented into the EMEP MSC-W chemistry-transport model. The results of these studies are presented and used to illustrate the global-scale impacts of the mechanistic updates on HOx radical concentrations.

The wet deposition of nitrogen and sulfur in Europe for the period 1990–2010 was estimated by six atmospheric chemistry transport models (CHIMERE, CMAQ, EMEP MSC-W, LOTOS-EUROS, MATCH and MINNI) within the framework of the EURODELTA-Trends model intercomparison. The simulated wet deposition and its trends for two 11-year periods (1990–2000 and 2000–2010) were evaluated using data from observations from the EMEP European monitoring network. For annual wet deposition of oxidised nitrogen (WNOx), model bias was within 30 % of the average of the observations for most models. There was a tendency for most models to underestimate annual wet deposition of reduced nitrogen (WNHx), although the model bias was within 40 % of the average of the observations. Model bias for WNHx was inversely correlated with model bias for atmospheric concentrations of NH3+NH4+, suggesting that an underestimation of wet deposition partially contributed to an overestimation of atmospheric concentrations. Model bias was also within about 40 % of the average of the observations for the annual wet deposition of sulfur (WSOx) for most models. Decreasing trends in WNOx were observed at most sites for both 11-year periods, with larger trends, on average, for the second period. The models also estimated predominantly decreasing trends at the monitoring sites and all but one of the models estimated larger trends, on average, for the second period. Decreasing trends were also observed at most sites for WNHx, although larger trends, on average, were observed for the first period. This pattern was not reproduced by the models, which estimated smaller decreasing trends, on average, than those observed or even small increasing trends. The largest observed trends were for WSOx, with decreasing trends at more than 80 % of the sites. On average, the observed trends were larger for the first period. All models were able to reproduce this pattern, although some models underestimated the trends (by up to a factor of 4) and others overestimated them (by up to 40 %), on average. These biases in modelled trends were directly related to the tendency of the models to under- or overestimate annual wet deposition and were smaller for the relative trends (expressed as % yr−1 relative to the deposition at the start of the period). The fact that model biases were fairly constant throughout the time series makes it possible to improve the predictions of wet deposition for future scenarios by adjusting the model estimates using a bias correction calculated from past observations. An analysis of the contributions of various factors to the modelled trends suggests that the predominantly decreasing trends in wet deposition are mostly due to reductions in emissions of the precursors NOx, NH3 and SOx. However, changes in meteorology (e.g. precipitation) and other (non-linear) interactions partially offset the decreasing trends due to emission reductions during the first period but not the second. This suggests that the emission reduction measures had a relatively larger effect on wet deposition during the second period, at least for the sites with observations.

In the framework of the EURODELTA-Trends (EDT) modeling experiment, several chemical transport models (CTMs) were applied for the 1990–2010 period to investigate air quality changes in Europe as well as the capability of the models to reproduce observed long-term air quality trends. Five CTMs have provided modeled air quality data for 21 continuous years in Europe using emission scenarios prepared by the International Institute for Applied Systems Analysis/Greenhouse Gas – Air Pollution Interactions and Synergies (IIASA/GAINS) and corresponding year-by-year meteorology derived from ERA-Interim global reanalysis. For this study, long-term observations of particle sulfate (SO42-), total nitrate (TNO3), total ammonium (TNHx) as well as sulfur dioxide (SO2) and nitrogen dioxide (NO2) for multiple sites in Europe were used to evaluate the model results. The trend analysis was performed for the full 21 years (referred to as PT) but also for two 11-year subperiods: 1990–2000 (referred to as P1) and 2000–2010 (referred to as P2). The experiment revealed that the models were able to reproduce the faster decline in observed SO2 concentrations during the first decade, i.e., 1990–2000, with a 64 %–76 % mean relative reduction in SO2 concentrations indicated by the EDT experiment (range of all the models) versus an 82 % mean relative reduction in observed concentrations. During the second decade (P2), the models estimated a mean relative reduction in SO2 concentrations of about 34 %–54 %, which was also in line with that observed (47 %). Comparisons of observed and modeled NO2 trends revealed a mean relative decrease of 25 % and between 19 % and 23 % (range of all the models) during the P1 period, and 12 % and between 22 % and 26 % (range of all the models) during the P2 period, respectively. Comparisons of observed and modeled trends in SO42- concentrations during the P1 period indicated that the models were able to reproduce the observed trends at most of the sites, with a 42 %–54 % mean relative reduction indicated by the EDT experiment (range of all models) versus a 57 % mean relative reduction in observed concentrations and with good performance also during the P2 and PT periods, even though all the models overpredicted the number of statistically significant decreasing trends during the P2 period. Moreover, especially during the P1 period, both modeled and observational data indicated smaller reductions in SO42- concentrations compared with their gas-phase precursor (i.e., SO2), which could be mainly attributed to increased oxidant levels and pH-dependent cloud chemistry. An analysis of the trends in TNO3 concentrations indicated a 28 %–39 % and 29 % mean relative reduction in TNO3 concentrations for the full period for model data (range of all the models) and observations, respectively. Further analysis of the trends in modeled HNO3 and particle nitrate (NO3-) concentrations revealed that the relative reduction in HNO3 was larger than that for NO3- during the P1 period, which was mainly attributed to an increased availability of “free ammonia”. By contrast, trends in modeled HNO3 and NO3- concentrations were more comparable during the P2 period. Also, trends of TNHx concentrations were, in general, underpredicted by all models, with worse performance for the P1 period than for P2. Trends in modeled anthropogenic and biogenic secondary organic aerosol (ASOA and BSOA) concentrations together with the trends in available emissions of biogenic volatile organic compounds (BVOCs) were also investigated. A strong decrease in ASOA was indicated by all the models, following the reduction in anthropogenic non-methane VOC (NMVOC) precursors. Biogenic emission data provided by the modeling teams indicated a few areas with statistically significant increase in isoprene emissions and monoterpene emissions during the 1990–2010 period over Fennoscandia and eastern European regions (i.e., around 14 %–27 %), which was mainly attributed to the increase of surface temperature. However, the modeled BSOA concentrations did not linearly follow the increase in biogenic emissions. Finally, a comprehensive evaluation against positive matrix factorization (PMF) data, available during the second period (P2) at various European sites, revealed a systematic underestimation of the modeled SOA fractions of a factor of 3 to 11, on average, most likely because of missing SOA precursors and formation pathways, with reduced biases for the models that accounted for chemical aging of semi-volatile SOA components in the atmosphere.

Figure S1: Spatial distribution of the observational sites for SOA (retrieved from PMF analysis).Total number of sites is 48.Sites with averages concentration above 7 µg m -3 over the measuring period were excluded from the analysis.Information on the sites and periods of the measurements are reported in Table S2.

Pedogenic processes imprint their signature on soils over the course of thousands to millions of years in most soil systems. Variation in soil forming processes – such as parent material weathering, organic material additions, hydrologic processes, and atmospheric additions – account for the distribution and sourcing of cations in ecosystems, and hence exert a strong influence on ecosystem productivity. Soil nutrient dynamics of cations also provide an indication of the dominant soil forming processes at work in a particular system. To gain insight into the generation and distribution of the soil cation pool in the Fraser Experimental Forest (FEF), we combined geochemical mass balance techniques and isotopic analyses of soil geochemical data to pedons across eight soil catenas in complex mountain terrain typical of the central Rocky Mountains. We found that mass gains in the FEF soils are primarily attributable to pedogenic additions of Ca to the soil mantle via atmospheric dust, and specifically that soil catenas on the summit landscapes were most enriched in Ca. Our data also show that atmospheric deposition contributions (calculated using Sr isotope ratios) to soils is as high as 82% (±3% SD), and that this isotopic signature in A-horizons and subsurface soil horizons diverges along a soil catena, due to both vertical and lateral hydrologic redistribution processes. Our results suggest that long term soil development and associated chemical signatures at the FEF are principally driven by the coupling of landscape scale cation supply processes, snow distribution, and snowmelt dynamics. Soil development models describing pedogenesis across catenas in montane ecosystems must pay special attention to atmospheric inputs and their redistribution. Any changes to these dynamics will affect productivity and soil/water chemistry in such ecosystems as investigated here.

Alkali-containing submicron particles were measured continuously during three months, including late winter and spring seasons in Gothenburg, Sweden. The overall aims were to characterize the ambient concentrations of combustion-related aerosol particles and to address the importance of local emissions and long-range transport for atmospheric concentrations in the urban background environment. K and Na concentrations in the particulate matter PM1 size range were measured by an Alkali aerosol mass spectrometer (Alkali-AMS) and a cluster analysis was conducted. Local meteorological conditions and trace gas and PM concentrations were also obtained for a nearby location. In addition, back trajectory analyses and chemical transport model (CTM) simulations were included for the evaluation. The Alkali-AMS cluster analysis indicated three major clusters: (1) biomass burning origin, (2) mixture of other combustion sources, and (3) marine origin. Low temperatures and low wind speed conditions correlated with high concentrations of K-containing particles, mainly owing to local and regional emissions from residential biomass combustion; transport of air masses from continental Europe also contribute to Cluster 1. The CTM results indicate that open biomass burning in the eastern parts of Europe may have contributed substantially to high PM2.5 concentrations (and to Cluster 1) during an episode in late March. According to the CTM results, the mixed cluster (2) is likely to include particles emitted from different source types and no single geographical source region seems to dominate for this cluster. The back trajectory analysis and meteorological conditions indicated that the marine origin cluster was correlated with westerly winds and high wind speed; this cluster had high concentrations of Na-containing particles, as expected for sea salt particles.

Biogenic volatile organic compounds (VOC) are important secondary organic aerosol (SOA) precursors. Whilst isoprene dominates VOC plant emissions globally, its yield of SOA mass is found to be modest in comparison to that of monoterpenes (MT). Tracers from isoprene oxidation have been observed in particles showing that they condense from the gas phase and yet new particle formation is suppressed by the presence of isoprene in mixtures of plant emissions containing MT. Experiments were performed in the JPAC chamber in Jülich. We showed that isoprene can suppress both the instantaneous mass formation and overall yield of monoterpenes in mixtures by two effects: oxidant and product scavenging. Isoprene scavenged OH radicals from reacting with MT (oxidant scavenging). Subsequently, the resulting isoprene peroxy radicals reacted with highly oxygenated peroxy radicals from MT oxidation (product scavenging). These effects from isoprene, also demonstrated using CO or CH4, reduced the yield of low-volatility, highly oxygenated molecules (HOM) from MT that would otherwise form SOA. Our results show that in mixtures changes in particle mass and number are not additive, and yields from single precursor experiments cannot simply be linearly combined. Reactive, modest SOA yield compounds are not necessarily net SOA producers and isoprene oxidation can suppress both SOA number and mass. Global model calculations support that OH scavenging and product scavenging can also operate in the real atmosphere. Our results highlight a need for more realistic consideration of SOA formation in the atmosphere analogous to the treatment of ozone formation, where interactions between the mechanistic pathways involving peroxy radicals are recognised to be essential.

The implementation of European emission abatement strategies has led to a significant reduction in the emissions of ozone precursors during the last decade. Ground-level ozone is also influenced by meteorological factors such as temperature, which exhibit interannual variability and are expected to change in the future. The impacts of climate change on air quality are usually investigated through air-quality models that simulate interactions between emissions, meteorology and chemistry. Within a multi-model assessment, this study aims to better understand how air-quality models represent the relationship between meteorological variables and surface ozone concentrations over Europe. A multiple linear regression (MLR) approach is applied to observed and modelled time series across 10 European regions in springtime and summertime for the period of 2000–2010 for both models and observations. Overall, the air-quality models are in better agreement with observations in summertime than in springtime and particularly in certain regions, such as France, central Europe or eastern Europe, where local meteorological variables show a strong influence on surface ozone concentrations. Larger discrepancies are found for the southern regions, such as the Balkans, the Iberian Peninsula and the Mediterranean basin, especially in springtime. We show that the air-quality models do not properly reproduce the sensitivity of surface ozone to some of the main meteorological drivers, such as maximum temperature, relative humidity and surface solar radiation. Specifically, all air-quality models show more limitations in capturing the strength of the ozone–relative-humidity relationship detected in the observed time series in most of the regions, for both seasons. Here, we speculate that dry-deposition schemes in the air-quality models might play an essential role in capturing this relationship. We further quantify the relationship between ozone and maximum temperature (mo3 − T, climate penalty) in observations and air-quality models. In summertime, most of the air-quality models are able to reproduce the observed climate penalty reasonably well in certain regions such as France, central Europe and northern Italy. However, larger discrepancies are found in springtime, where air-quality models tend to overestimate the magnitude of the observed climate penalty.

Source apportionment (SA) of carbonaceous aerosol was performed as part of the EMEP Intensive Measurement Periods (EIMPs), conducted in fall 2008 and winter/spring 2009. Levels of elemental carbon (EC), particulate organic carbon (OCp), particulate total carbon (TCp), levoglucosan and 14C in PM10, observed at nine European rural background sites, were used as input for the SA, whereas Latin Hypercube Sampling (LHS) was used to statistically treat the multitude of possible combinations resulting when ambient concentrations were combined with appropriate emission ratios. Five predefined sources/subcategories of carbonaceous aerosol were apportioned: Elemental and organic carbon from combustion of biomass (ECbb and OCbb) and from fossil fuel (ECff and OCff) sources, as well as remaining non-fossil organic carbon (OCrnf), typically dominated by natural sources. The carbonaceous aerosol concentration decreased from South to North, as did the concentration of the apportioned carbonaceous aerosol. OCrnf was more abundant in fall compared to winter/spring, reflecting the vegetative season, and made a larger contribution to TCp than anthropogenic sources (here: ECbb, OCbb, ECff and OCff) at four of the sites, whereas anthropogenic sources dominated at all but one sites in winter/spring. Levels of OCbb and ECbb were typically higher in winter/spring than in fall, due to larger residential wood burning emissions in the heating season, whereas there was no consistent seasonal pattern for fossil fuel emissions. Biomass burning (OCbb + ECbb) was the major anthropogenic source at the Central European sites in fall, whereas fossil fuel sources dominated at the southernmost and the two northernmost sites. In winter/spring, biomass burning was the major anthropogenic source at all but two sites. Addressing EC in particular, fossil fuel sources dominated at all sites in fall, whereas there was as shift towards biomass burning in winter/spring for the southernmost sites. Influence of residential wood burning emissions was substantial already in the first week of sampling in fall, constituting 30–50 % of TCp at most sites, showing that this source can be dominating even at a time of the year when the ambient temperature in Europe is still rather high. Model calculations were made, attempting to reproduce LHS-derived OCbb and ECbb, using two different residential wood burning emission inventories. Both simulations strongly under-predicted the LHS-derived values at most sites outside Scandinavia. Emissions based on a consistent bottom-up inventory for residential combustion (and including intermediate volatility compounds, IVOC) improved model results at most sites compared to the base-case emissions (based mainly on officially reported national emissions), but at the three southernmost sites the modelled OCbb and ECbb concentrations were still much lower than the LHS source apportioned results. The current study shows that natural sources is a major contributor to the carbonaceous aerosol in Europe even in fall and in winter/spring, and that residential wood burning emissions can be equally large or larger than that of fossil fuel sources, depending on season and region. Our results suggest that residential wood burning emissions are still poorly constrained for large parts of Europe. The need to improve emission inventories is obvious, with harmonization of emission factors between countries likely being the most important step to improve model calculations, not only for biomass burning emissions, but for European PM2.5 concentrations in general.