We present a new European plant-specific emission inventory for isoprene, monoterpenes, sesquiterpenes and oxygenated VOC (OVOC), on a spatial resolution of 0.089×0.089 degrees, for implementation in atmospheric transport models. The inventory incorporates more accurate data on foliar biomass densities from several litterfall databases that became available in the last years for the main tree species in Europe. A bioclimatic correction factor was introduced to correct the foliar biomass densities of trees and crops for the different plant growth conditions that can be found in Pan-Europe. Long-term seasonal variability of agriculture and forest emissions was taken into account by implementing a new growing season concept. The 2004–2005 averaged annual total biogenic volatile organic compound (BVOC) emissions for the Pan-European domain are estimated to be about 12 Tg with a large contribution from the OVOC class of about 4.5 Tg and from monoterpenes of about 4 Tg. Annual isoprene emissions are found to be about 3.5 Tg, insensitive to the chosen emission algorithm. Emissions of OVOC were found to originate to a large extent from agriculture. Further experiments on crop emissions should be carried out to check the validity of the applied standard emission factors. The new inventory aims at a fully transparent and verifiable aggregation of detailed land use information and at the inclusion of plant-specific emission data. Though plant-specific land use data is available with relatively high accuracy, a lack of experimental biomass densities and emission data on terpenes, sesquiterpenes and oxygenated VOC, in particular for agricultural plants, currently limits the setup of a highly accurate plant-specific emission inventory.

Our understanding of the global black carbon (BC) cycle is essentially qualitative due to uncertainties in our knowledge of its properties. This work investigates two source of uncertainties in modelling black carbon: those due to the use of different schemes for BC ageing and its removal rate in the global Transport-Chemistry model TM5 and those due to the uncertainties in the definition and quantification of the observations, which propagate through to both the emission inventories, and the measurements used for the model evaluation. The schemes for the atmospheric processing of black carbon that have been tested with the model are (i) a simple approach considering BC as bulk aerosol and a simple treatment of the removal with fixed 70% of in-cloud black carbon concentrations scavenged by clouds and removed when rain is present and (ii) a more complete description of microphysical ageing within an aerosol dynamics model, where removal is coupled to the microphysical properties of the aerosol, which results in a global average of 40% in-cloud black carbon that is scavenged in clouds and subsequently removed by rain, thus resulting in a longer atmospheric lifetime. This difference is reflected in comparisons between both sets of modelled results and the measurements. Close to the sources, both anthropogenic and vegetation fire source regions, the model results do not differ significantly, indicating that the emissions are the prevailing mechanism determining the concentrations and the choice of the aerosol scheme does not influence the levels. In more remote areas such as oceanic and polar regions the differences can be orders of magnitude, due to the differences between the two schemes. The more complete description reproduces the seasonal trend of the black carbon observations in those areas, although not always the magnitude of the signal, while the more simplified approach underestimates black carbon concentrations by orders of magnitude. The sensitivity to wet scavenging has been tested by varying in-cloud and below-cloud removal. BC lifetime increases by 10% when large scale and convective scale precipitation removal efficiency are reduced by 30%, while the variation is very small when below-cloud scavenging is zero. Since the emission inventories are representative of elemental carbon-like substance, the model output should be compared to elemental carbon measurements and if known, the ratio of black carbon to elemental carbon mass should be taken into account when the model is compared with black carbon observations.

The source contributions to carbonaceous PM_2.5 aerosol were investigated at a European background site at the edge of the Po Valley, in Northern Italy, during the period January–December 2007. Carbonaceous aerosol was described as the sum of 8 source components: primary (1) and secondary (2) biomass burning organic carbon, biomass burning elemental carbon (3), primary (4) and secondary (5) fossil organic carbon, fossil fuel burning elemental carbon (6), primary (7) and secondary (8) biogenic organic carbon. The mass concentration of each component was quantified using a set of macro tracers (organic carbon OC, elemental carbon EC, and levoglucosan), micro tracers (arabitol and mannitol), and ¹⁴C measurements. This was the first time that ¹⁴C measurements covered a full annual cycle with daily resolution. This set of 6 tracers, together with assumed uncertainty ranges of the ratios of OC-to-EC, and the reference fraction of modern carbon in the 8 source categories, provides strong constraints to the source contributions to carbonaceous aerosol. The uncertainty of contributions was assessed with a Quasi-Monte Carlo (QMC) method accounting for the variability of OC and EC emission factors, the uncertainty of reference fractions of modern carbon, and the measurement uncertainty. During winter, biomass burning composed 64 % (±15 %) of the total carbon (TC) concentration, while in summer secondary biogenic OC accounted for 50 % (±16 %) of TC. The contribution of primary biogenic aerosol particles was negligible during the entire year. Moreover, aerosol associated with fossil sources represented 27 % (±16 %) and 41 % (±26 %) of TC in winter and summer, respectively. The contribution of secondary organic aerosol (SOA) to the organic mass (OM) was significant during the entire year. SOA accounted for 30 % (±16 %) and 85 % (±12 %) of OM during winter and summer, respectively. While the summer SOA was dominated by biogenic sources, winter SOA was mainly due to biomass burning and fossil sources. This indicates that the oxidation of semi-volatile and intermediate volatility organic compounds co-emitted with primary organics is a significant source of SOA, as suggested by recent model results and Aerosol Mass Spectrometer measurements. Comparison with previous global model simulations, indicates a strong underestimate of wintertime primary aerosol emissions in this region. The comparison of source apportionment results in different urban and rural areas showed that the sampling site was mainly affected by local aerosol sources during winter and regional air masses from the nearby Po Valley in summer. This observation was further confirmed by back-trajectory analysis applying the Potential Source Contribution Function method to identify potential source regions.

The Baltic Sea is a highly frequented shipping area with busy shipping lanes close to densely populated regions. Exhaust emissions from ship traffic into the atmosphere do not only enhance air pollution, they also affect the Baltic Sea environment through acidification and eutrophication of marine waters and surrounding terrestrial ecosystems. As part of the European BONUS project SHEBA (Sustainable Shipping and Environment of the Baltic Sea region), the transport, chemical transformation and fate of atmospheric pollutants in the Baltic Sea region were simulated with three regional chemistry transport model (CTM) systems, CMAQ, EMEP/MSC-W and SILAM, with grid resolutions between 4 and 11 km. The main goal was to quantify the effect that shipping emissions have on the regional air quality in the Baltic Sea region when the same shipping emission dataset but different CTMs are used in their typical set-ups. The performance of these models and the shipping contribution to the results of the individual models were evaluated for sulfur dioxide (SO₂), nitrogen dioxide (NO₂), ozone (O₃) and particulate matter (PM_2.5). Model results from the three CTMs for total air pollutant concentrations were compared to observations from rural and urban background stations of the AirBase monitoring network in the coastal areas of the Baltic Sea region. Observed PM_2.5 in summer was underestimated strongly by CMAQ and to some extent by EMEP/MSC-W. Observed PM_2.5 in winter was underestimated by SILAM. In autumn all models were in better agreement with observed PM_2.5. The spatial average of the annual mean O₃ in the EMEP/MSC-W simulation was ca. 20 % higher compared to the other two simulations, which is mainly the consequence of using a different set of boundary conditions for the European model domain. There are significant differences in the calculated ship contributions to the levels of air pollutants among the three models. EMEP/MSC-W, with the coarsest grid, predicted weaker ozone depletion through NO emissions in the proximity of the main shipping routes than the other two models. The average contribution of ships to PM_2.5 levels in coastal land areas is in the range of 3.1 %–5.7 % for the three CTMs. Differences in ship-related PM_2.5 between the models are mainly attributed to differences in the schemes for inorganic aerosol formation. Differences in the ship-related elemental carbon (EC) among the CTMs can be explained by differences in the meteorological conditions, atmospheric transport processes and the applied wet-scavenging parameterizations. Overall, results from the present study show the sensitivity of the ship contribution to combined uncertainties in boundary conditions, meteorological data and aerosol formation and deposition schemes. This is an important step towards a more reliable evaluation of policy options regarding emission regulations for ship traffic and the planned introduction of a nitrogen emission control area (NECA) in the Baltic Sea and the North Sea in 2021.