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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.

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.

Carbonaceous aerosol (total carbon, TCp) was source apportioned at nine European rural background sites, as part of the European Measurement and Evaluation Programme (EMEP) Intensive Measurement Periods in fall 2008 and winter/spring 2009. Five predefined fractions were apportioned based on ambient measurements: elemental and organic carbon, from combustion of biomass (ECbb and OCbb) and from fossil-fuel (ECff and OCff) sources, and remaining non-fossil organic carbon (OCrnf), dominated by natural sources.OCrnf made a larger contribution to TCp than anthropogenic sources (ECbb, OCbb, ECff, and OCff) at four out of nine sites in fall, reflecting the vegetative season, whereas anthropogenic sources dominated at all but one site in winter/spring. Biomass burning (OCbb + ECbb) was the major anthropogenic source at the central European sites in fall, whereas fossil-fuel (OCff + ECff) sources dominated at the southernmost and the two northernmost sites. Residential wood burning emissions explained 30 %–50 % of TCp at most sites in the first week of sampling in fall, showing that this source can be the dominant one, even outside the heating season. In winter/spring, biomass burning was the major anthropogenic source at all but two sites, reflecting increased residential wood burning emissions in the heating season. Fossil-fuel sources dominated EC at all sites in fall, whereas there was a shift towards biomass burning for the southernmost sites in winter/spring.Model calculations based on base-case emissions (mainly officially reported national emissions) strongly underpredicted observational derived levels of OCbb and ECbb outside Scandinavia. Emissions based on a consistent bottom-up inventory for residential wood burning (and including intermediate volatility compounds, IVOCs) improved model results compared to the base-case emissions, but modeled levels were still substantially underestimated compared to observational derived OCbb and ECbb levels at the southernmost sites.Our study shows that natural sources are a major contributor to carbonaceous aerosol in Europe, even in fall and in winter/spring, and that residential wood burning emissions are equally as large as or larger than that of fossil-fuel sources, depending on season and region. The poorly constrained residential wood burning emissions for large parts of Europe show the obvious need to improve emission inventories, with harmonization of emission factors between countries likely being the most important step to improve model calculations for biomass burning emissions, and European PM2.5 concentrations in general.

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.

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.

The EURODELTA-Trends multi-model chemistry-transport experiment has been designed to facilitate a better understanding of the evolution of air pollution and its drivers for the period 1990–2010 in Europe. The main objective of the experiment is to assess the efficiency of air pollutant emissions mitigation measures in improving regional-scale air quality. The present paper formulates the main scientific questions and policy issues being addressed by the EURODELTA-Trends modelling experiment with an emphasis on how the design and technical features of the modelling experiment answer these questions. The experiment is designed in three tiers, with increasing degrees of computational demand in order to facilitate the participation of as many modelling teams as possible. The basic experiment consists of simulations for the years 1990, 2000, and 2010. Sensitivity analysis for the same three years using various combinations of (i) anthropogenic emissions, (ii) chemical boundary conditions, and (iii) meteorology complements it. The most demanding tier consists of two complete time series from 1990 to 2010, simulated using either time-varying emissions for corresponding years or constant emissions. Eight chemistry-transport models have contributed with calculation results to at least one experiment tier, and five models have – to date – completed the full set of simulations (and 21-year trend calculations have been performed by four models). The modelling results are publicly available for further use by the scientific community. The main expected outcomes are (i) an evaluation of the models' performances for the three reference years, (ii) an evaluation of the skill of the models in capturing observed air pollution trends for the 1990–2010 time period, (iii) attribution analyses of the respective role of driving factors (e.g. emissions, boundary conditions, meteorology), (iv) a dataset based on a multi-model approach, to provide more robust model results for use in impact studies related to human health, ecosystem, and radiative forcing.

With the present demand on fast and inexpensive aerosol source apportionment methods, the Aethalometer model was evaluated for a full seasonal cycle (June 2014–June 2015) at a rural atmospheric measurement station in southern Sweden by using radiocarbon and levoglucosan measurements. By utilizing differences in absorption of UV and IR, the Aethalometer model apportions carbon mass into wood burning (WB) and fossil fuel combustion (FF) aerosol. In this study, a small modification in the model in conjunction with carbon measurements from thermal–optical analysis allowed apportioned non-light-absorbing biogenic aerosol to vary in time. The absorption differences between WB and FF can be quantified by the absorption Ångström exponent (AAE). In this study AAEWB was set to 1.81 and AAEFF to 1.0. Our observations show that the AAE was elevated during winter (1.36 ± 0.07) compared to summer (1.12 ± 0.07). Quantified WB aerosol showed good agreement with levoglucosan concentrations, both in terms of correlation (R2 = 0. 70) and in comparison to reference emission inventories. WB aerosol showed strong seasonal variation with high concentrations during winter (0.65 µg m−3, 56 % of total carbon) and low concentrations during summer (0.07 µg m−3, 6 % of total carbon). FF aerosol showed less seasonal dependence; however, black carbon (BC) FF showed clear diurnal patterns corresponding to traffic rush hour peaks. The presumed non-light-absorbing biogenic carbonaceous aerosol concentration was high during summer (1.04 µg m−3, 72 % of total carbon) and low during winter (0.13 µg m−3, 8 % of total carbon). Aethalometer model results were further compared to radiocarbon and levoglucosan source apportionment results. The comparison showed good agreement for apportioned mass of WB and biogenic carbonaceous aerosol, but discrepancies were found for FF aerosol mass. The Aethalometer model overestimated FF aerosol mass by a factor of 1.3 compared to radiocarbon and levoglucosan source apportionment. A performed sensitivity analysis suggests that this discrepancy can be explained by interference of non-light-absorbing biogenic carbon during winter. In summary, the Aethalometer model offers a cost-effective yet robust high-time-resolution source apportionment at rural background stations compared to a radiocarbon and levoglucosan alternative.

We present high-resolution (5 km × 5 km) atmospheric chemical transport model (ACTM) simulations of the impact of newly estimated traffic-related emissions on secondary organic aerosol (SOA) formation over the UK for 2012. Our simulations include additional diesel-related intermediate-volatility organic compound (IVOC) emissions derived directly from comprehensive field measurements at an urban background site in London during the 2012 Clean Air for London (ClearfLo) campaign. Our IVOC emissions are added proportionally to VOC emissions, as opposed to proportionally to primary organic aerosol (POA) as has been done by previous ACTM studies seeking to simulate the effects of these missing emissions. Modelled concentrations are evaluated against hourly and daily measurements of organic aerosol (OA) components derived from aerosol mass spectrometer (AMS) measurements also made during the ClearfLo campaign at three sites in the London area. According to the model simulations, diesel-related IVOCs can explain on average ∼ 30 % of the annual SOA in and around London. Furthermore, the 90th percentile of modelled daily SOA concentrations for the whole year is 3.8 µg m−3, constituting a notable addition to total particulate matter. More measurements of these precursors (currently not included in official emissions inventories) is recommended. During the period of concurrent measurements, SOA concentrations at the Detling rural background location east of London were greater than at the central London location. The model shows that this was caused by an intense pollution plume with a strong gradient of imported SOA passing over the rural location. This demonstrates the value of modelling for supporting the interpretation of measurements taken at different sites or for short durations.

This paper describes the pre-operational analysis and forecasting system developed during MACC (Monitoring Atmospheric Composition and Climate) and continued in the MACC-II (Monitoring Atmospheric Composition and Climate: Interim Implementation) European projects to provide air quality services for the European continent. This system is based on seven state-of-the art models developed and run in Europe (CHIMERE, EMEP, EURAD-IM, LOTOS-EUROS, MATCH, MOCAGE and SILAM). These models are used to calculate multi-model ensemble products. The paper gives an overall picture of its status at the end of MACC-II (summer 2014) and analyses the performance of the multi-model ensemble. The MACC-II system provides daily 96 h forecasts with hourly outputs of 10 chemical species/aerosols (O3, NO2, SO2, CO, PM10, PM2.5, NO, NH3, total NMVOCs (non-methane volatile organic compounds) and PAN+PAN precursors) over eight vertical levels from the surface to 5 km height. The hourly analysis at the surface is done a posteriori for the past day using a selection of representative air quality data from European monitoring stations. The performance of the system is assessed daily, weekly and every 3 months (seasonally) through statistical indicators calculated using the available representative air quality data from European monitoring stations. Results for a case study show the ability of the ensemble median to forecast regional ozone pollution events. The seasonal performances of the individual models and of the multi-model ensemble have been monitored since September 2009 for ozone, NO2 and PM10. The statistical indicators for ozone in summer 2014 show that the ensemble median gives on average the best performances compared to the seven models. There is very little degradation of the scores with the forecast day but there is a marked diurnal cycle, similarly to the individual models, that can be related partly to the prescribed diurnal variations of anthropogenic emissions in the models. During summer 2014, the diurnal ozone maximum is underestimated by the ensemble median by about 4 μg m−3 on average. Locally, during the studied ozone episodes, the maxima from the ensemble median are often lower than observations by 30–50 μg m−3. Overall, ozone scores are generally good with average values for the normalised indicators of 0.14 for the modified normalised mean bias and of 0.30 for the fractional gross error. Tests have also shown that the ensemble median is robust to reduction of ensemble size by one, that is, if predictions are unavailable from one model. Scores are also discussed for PM10 for winter 2013–1014. There is an underestimation of most models leading the ensemble median to a mean bias of −4.5 μg m−3. The ensemble median fractional gross error is larger for PM10 (~ 0.52) than for ozone and the correlation is lower (~ 0.35 for PM10 and ~ 0.54 for ozone). This is related to a larger spread of the seven model scores for PM10 than for ozone linked to different levels of complexity of aerosol representation in the individual models. In parallel, a scientific analysis of the results of the seven models and of the ensemble is also done over the Mediterranean area because of the specificity of its meteorology and emissions. The system is robust in terms of the production availability. Major efforts have been done in MACC-II towards the operationalisation of all its components. Foreseen developments and research for improving its performances are discussed in the conclusion.

Currently residential wood combustion (RWC) is increasing in Europe because of rising fossil fuel prices but also due to climate change mitigation policies. However, especially in small-scale applications, RWC may cause high emissions of particulate matter (PM). Recently we have developed a new high-resolution (7 × 7 km) anthropogenic carbonaceous aerosol emission inventory for Europe. The inventory indicated that about half of the total PM2.5 emission in Europe is carbonaceous aerosol and identified RWC as the largest organic aerosol source in Europe. The inventory was partly based on national reported PM emissions. Use of this organic aerosol inventory as input for two chemical transport models (CTMs), PMCAMx and EMEP MSC-W, revealed major underestimations of organic aerosol in winter time, especially for regions dominated by RWC. Interestingly, this was not universal but appeared to differ by country. In the present study we constructed a revised bottom-up emission inventory for RWC accounting for the semivolatile components of the emissions. The revised RWC emissions are higher than those in the previous inventory by a factor of 2–3 but with substantial inter-country variation. The new emission inventory served as input for the CTMs and a substantially improved agreement between measured and predicted organic aerosol was found. The revised RWC inventory improves the model-calculated organic aerosol significantly. Comparisons to Scandinavian source apportionment studies also indicate substantial improvements in the modelled wood-burning component of organic aerosol. This suggests that primary organic aerosol emission inventories need to be revised to include the semivolatile organic aerosol that is formed almost instantaneously due to dilution and cooling of the flue gas or exhaust. Since RWC is a key source of fine PM in Europe, a major revision of the emission estimates as proposed here is likely to influence source–receptor matrices and modelled source apportionment. Since usage of biofuels in small combustion units is a globally significant source, the findings presented here are also relevant for regions outside of Europe.

We have implemented the sectional aerosol dynamics model SALSA (Sectional Aerosol module for Large Scale Applications) in the European-scale chemistry-transport model MATCH (Multi-scale Atmospheric Transport and Chemistry). The new model is called MATCH-SALSA. It includes aerosol microphysics, with several formulations for nucleation, wet scavenging and condensation. The model reproduces observed higher particle number concentration (PNC) in central Europe and lower concentrations in remote regions. The modeled PNC size distribution peak occurs at the same or smaller particle size as the observed peak at four measurement sites spread across Europe. Total PNC is underestimated at northern and central European sites and accumulation-mode PNC is underestimated at all investigated sites. The low nucleation rate coefficient used in this study is an important reason for the underestimation. On the other hand, the model performs well for particle mass (including secondary inorganic aerosol components), while elemental and organic carbon concentrations are underestimated at many of the sites. Further development is needed, primarily for treatment of secondary organic aerosol, in terms of biogenic emissions and chemical transformation. Updating the biogenic secondary organic aerosol (SOA) scheme will likely have a large impact on modeled PM2.5 and also affect the model performance for PNC through impacts on nucleation and condensation.

We have investigated the potential impact on organic aerosol formation from biotic stress-induced emissions (SIE) of organic molecules from forests in Europe (north of lat. 45° N). Emission estimates for sesquiterpenes (SQT), methyl salicylate (MeSA) and unsaturated C17 compounds, due to different stressors, are based on experiments in the Jülich Plant Atmosphere Chamber (JPAC), combined with estimates of the fraction of stressed trees in Europe based on reported observed tree damage. SIE were introduced in the EMEP MSC-W chemical transport model and secondary organic aerosol (SOA) yields from the SIE were taken from the JPAC experiments. Based on estimates of current levels of infestation and the JPAC aerosol yields, the model results suggest that the contribution to SOA in large parts of Europe may be substantial. It is possible that SIE contributes as much, or more, to organic aerosol than the constitutive biogenic VOC emissions, at least during some periods. Based on the assumptions in this study, SIE-SOA are estimated to constitute between 50 and 70 % of the total biogenic SOA (BSOA) in a current-situation scenario where the biotic stress in northern and central European forests causes large SIE of MeSA and SQT. An alternative current-situation scenario with lower SIE, consisting solely of SQT, leads to lower SIE-SOA, between 20 and 40 % of the total BSOA. Hypothetical future scenarios with increased SIE, due to higher degrees of biotic stress, show that SOA formation due to SIE can become even larger. Unsaturated C17 BVOC (biogenic volatile organic compounds) emitted by spruce infested by the forest-honey generating bark louse, Cinara pilicornis, have a high SOA-forming potential. A model scenario investigating the effect of a regional, episodic infestation of Cinara pilicornis in Baden-Württemberg, corresponding to a year with high production of forest honey, shows that these types of events could lead to very large organic aerosol formation in the infested region. We have used the best available laboratory data on biotic SIE applicable to northern and central European forests. Using these data and associated assumptions, we have shown that SIE are potentially important for SOA formation but the magnitude of the impact is uncertain and needs to be constrained by further laboratory, field and modelling studies. As an example, the MeSA, which is released as a consequence of various types of biotic stress, is found to have a potentially large impact on SIE-SOA in Europe, but different assumptions regarding the nighttime chemistry of MeSA can change its SOA potential substantially. Thus, further investigations of the atmospheric chemistry of MeSA and observational field studies are needed to clarify the role of this compound in the atmosphere.

The atmospheric concentration of elemental carbon (EC) in Europe during the six-year period 2005–2010 has been simulated with the EMEP MSC-W model. The model bias compared to EC measurements was less than 20% for most of the examined sites. The model results suggest that fossil fuel combustion is the dominant source of EC in most of Europe but that there are important contributions also from residential wood burning during the cold seasons and, during certain episodes, also from open biomass burning (wildfires and agricultural fires). The modelled contributions from open biomass fires to ground level concentrations of EC were small at the sites included in the present study, 10. The modelling of this EC source is subject to many uncertainties, and it was likely underestimated for some episodes. EC measurements and modelled EC were also compared to optical measurements of black carbon (BC). The relationships between EC and BC (as given by mass absorption cross section, MAC, values) differed widely between the sites, and the correlation between observed EC and BC is sometimes poor, making it difficult to compare results using the two techniques and limiting the comparability of BC measurements to model EC results. A new bottom-up emission inventory for carbonaceous aerosol from residential wood combustion has been applied. For some countries the new inventory has substantially different EC emissions compared to earlier estimates. For northern Europe the most significant changes are much lower emissions in Norway and higher emissions in neighbouring Sweden and Finland. For Norway and Sweden, comparisons to source-apportionment data from winter campaigns indicate that the new inventory may improve model-calculated EC from wood burning. Finally, three different model setups were tested with variable atmospheric lifetimes of EC in order to evaluate the model sensitivity to the assumptions regarding hygroscopicity and atmospheric ageing of EC. The standard ageing scheme leads to a rapid transformation of the emitted hydrophobic EC to hygroscopic particles, and generates similar results when assuming that all EC is aged at the point of emission. Assuming hydrophobic emissions and no ageing leads to higher EC concentrations. For the more remote sites, the observed EC concentration was in between the modelled EC using standard ageing and the scenario treating EC as hydrophobic. This could indicate too-rapid EC ageing in the model in relatively clean parts of the atmosphere.

The first EMEP intensive measurement periods were held in June 2006 and January 2007. The measurements aimed to characterize the aerosol chemical compositions, including the gas/aerosol partitioning of inorganic compounds. The measurement program during these periods included daily or hourly measurements of the secondary inorganic components, with additional measurements of elemental- and organic carbon (EC and OC) and mineral dust in PM1, PM2.5 and PM10. These measurements have provided extended knowledge regarding the composition of particulate matter and the temporal and spatial variability of PM, as well as an extended database for the assessment of chemical transport models. This paper summarise the first experiences of making use of measurements from the first EMEP intensive measurement periods along with EMEP model results from the updated model version to characterise aerosol composition. We investigated how the PM chemical composition varies between the summer and the winter month and geographically. The observation and model data are in general agreement regarding the main features of PM10 and PM2.5 composition and the relative contribution of different components, though the EMEP model tends to give slightly lower estimates of PM10 and PM2.5 compared to measurements. The intensive measurement data has identified areas where improvements are needed. Hourly concurrent measurements of gaseous and particulate components for the first time facilitated testing of modelled diurnal variability of the gas/aerosol partitioning of nitrogen species. In general, the modelled diurnal cycles of nitrate and ammonium aerosols are in fair agreement with the measurements, but the diurnal variability of ammonia is not well captured. The largest differences between model and observations of aerosol mass are seen in Italy during winter, which to a large extent may be explained by an underestimation of residential wood burning sources. It should be noted that both primary and secondary OC has been included in the calculations for the first time, showing promising results. Mineral dust is important, especially in southern Europe, and the model seems to capture the dust episodes well. The lack of measurements of mineral dust hampers the possibility for model evaluation for this highly uncertain PM component. There are also lessons learnt regarding improved measurements for future intensive periods. There is a need for increased comparability between the measurements at different sites. For the nitrogen compounds it is clear that more measurements using artefact free methods based on continuous measurement methods and/or denuders are needed. For EC/OC, a reference methodology (both in field and laboratory) was lacking during these periods giving problems with comparability, though measurement protocols have recently been established and these should be followed by the Parties to the EMEP Protocol. For measurements with no defined protocols, it might be a good solution to use centralised laboratories to ensure comparability across the network. To cope with the introduction of these new measurements, new reporting guidelines have been developed to ensure that all proper information about the methodologies and data quality is given.

A new organic aerosol module has been implemented into the EMEP chemical transport model. Four different volatility basis set (VBS) schemes have been tested in long-term simulations for Europe, covering the six years 2002–2007. Different assumptions regarding partitioning of primary organic aerosol and aging of primary semi-volatile and intermediate volatility organic carbon (S/IVOC) species and secondary organic aerosol (SOA) have been explored. Model results are compared to filter measurements, aerosol mass spectrometry (AMS) data and source apportionment studies, as well as to other model studies. The present study indicates that many different sources contribute significantly to organic aerosol in Europe. Biogenic and anthropogenic SOA, residential wood combustion and vegetation fire emissions may all contribute more than 10% each over substantial parts of Europe. This study shows smaller contributions from biogenic SOA to organic aerosol in Europe than earlier work, but relatively greater anthropogenic SOA. Simple VBS based organic aerosol models can give reasonably good results for summer conditions but more observational studies are needed to constrain the VBS parameterisations and to help improve emission inventories. The volatility distribution of primary emissions is one important issue for further work. Emissions of volatile organic compounds from biogenic sources are also highly uncertain and need further validation. We can not reproduce winter levels of organic aerosol in Europe, and there are many indications that the present emission inventories substantially underestimate emissions from residential wood combustion in large parts of Europe.

The Meteorological Synthesizing Centre-West (MSC-W) of the European Monitoring and Evaluation Programme (EMEP) has been performing model calculations in support of the Convention on Long Range Transboundary Air Pollution (CLRTAP) for more than 30 years. The EMEP MSC-W chemical transport model is still one of the key tools within European air pollution policy assessments. Traditionally, the model has covered all of Europe with a resolution of about 50 km × 50 km, and extending vertically from ground level to the tropopause (100 hPa). The model has changed extensively over the last ten years, however, with flexible processing of chemical schemes, meteorological inputs, and with nesting capability: the code is now applied on scales ranging from local (ca. 5 km grid size) to global (with 1 degree resolution). The model is used to simulate photo-oxidants and both inorganic and organic aerosols. In 2008 the EMEP model was released for the first time as public domain code, along with all required input data for model runs for one year. The second release of the EMEP MSC-W model became available in mid 2011, and a new release is targeted for summer 2012. This publication is intended to document this third release of the EMEP MSC-W model. The model formulations are given, along with details of input data-sets which are used, and a brief background on some of the choices made in the formulation is presented. The model code itself is available at www.emep.int, along with the data required to run for a full year over Europe.

In this paper we describe and summarize the main achievements of the European Aerosol Cloud Climate and Air Quality Interactions project (EUCAARI). EUCAARI started on 1 January 2007 and ended on 31 December 2010 leaving a rich legacy including: (a) a comprehensive database with a year of observations of the physical, chemical and optical properties of aerosol particles over Europe, (b) comprehensive aerosol measurements in four developing countries, (c) a database of airborne measurements of aerosols and clouds over Europe during May 2008, (d) comprehensive modeling tools to study aerosol processes fron nano to global scale and their effects on climate and air quality. In addition a new Pan-European aerosol emissions inventory was developed and evaluated, a new cluster spectrometer was built and tested in the field and several new aerosol parameterizations and computations modules for chemical transport and global climate models were developed and evaluated. These achievements and related studies have substantially improved our understanding and reduced the uncertainties of aerosol radiative forcing and air quality-climate interactions. The EUCAARI results can be utilized in European and global environmental policy to assess the aerosol impacts and the corresponding abatement strategies.

A one-year study was performed at the Vavihill background station in southern Sweden to estimate the anthropogenic contribution to the carbonaceous aerosol. Weekly samples of the particulate matter PM10 were collected on quartz filters, and the amounts of organic carbon, elemental carbon, radiocarbon (14C) and levoglucosan were measured. This approach enabled source apportionment of the total carbon in the PM10 fraction using the concentration ratios of the sources. The sources considered in this study were emissions from the combustion of fossil fuels and biomass, as well as biogenic sources. During the summer, the carbonaceous aerosol mass was dominated by compounds of biogenic origin (80%), which are associated with biogenic primary and secondary organic aerosols. During the winter months, biomass combustion (32%) and fossil fuel combustion (28%) were the main contributors to the carbonaceous aerosol. Elemental carbon concentrations in winter were about twice as large as during summer, and can be attributed to biomass combustion, probably from domestic wood burning. The contribution of fossil fuels to elemental carbon was stable throughout the year, although the fossil contribution to organic carbon increased during the winter. Thus, the organic aerosol originated mainly from natural sources during the summer and from anthropogenic sources during the winter. The result of this source apportionment was compared with results from the EMEP MSC-W chemical transport model. The model and measurements were generally consistent for total atmospheric organic carbon, however, the contribution of the sources varied substantially. E.g. the biomass burning contributions of OC were underestimated by the model by a factor of 2.2 compared to the measurements.

Reprogramming somatic cells into a pluripotent state brings patient-tailored, ethical controversy-free cellular therapy closer to reality. However, stem cells and cancer cells share many common characteristics; therefore, it is crucial to be able to discriminate between them. We generated two induced pluripotent stem cell (iPSC) lines, with NANOG pre-transduction followed by OCT3/4, SOX2, and LIN28 overexpression. One of the cell lines, CHiPS W, showed normal pluripotent stem cell characteristics, while the other, CHiPS A, though expressing pluripotency markers, failed to differentiate and gave rise to germ cell-like tumours in vivo. Comparative genomic hybridisation analysis of the generated iPS lines revealed that they were genetically more stable than human embryonic stem cell counterparts. This analysis proved to be predictive for the differentiation potential of analysed cells. Moreover, the CHiPS A line expressed a lower ratio of p53/p21 when compared to CHiPS W. NANOG pre-induction followed by OCT3/4, SOX2, MYC, and KLF4 induction resulted in the same tumour-inducing phenotype. These results underline the importance of a re-examination of the role of NANOG during reprogramming. Moreover, this reprogramming method may provide insights into primordial cell tumour formation and cancer stem cell transformation.