Abstract.A method is presented for the evaluation of the exhaust emissions of marine traffic, based on the messages provided by the Automatic Identification System (AIS), which enable the positioning of ship emissions with a high spatial resolution (typically a few tens of metres). The model also takes into account the detailed technical data of each individual vessel. The previously developed model was applicable for evaluating the emissions of NO x , SO x and CO 2 . This paper addresses a substantial extension of the modelling system, to allow also for the mass-based emissions of particulate matter (PM) and carbon monoxide (CO). The presented Ship Traffic Emissions Assessment Model (STEAM2) allows for the influences of accurate travel routes and ship speed, engine load, fuel sulphur content, multiengine setups, abatement methods and waves. We address in particular the modeling of the influence on the emissions of both engine load and the sulphur content of the fuel. The presented methodology can be used to evaluate the total PM emissions, and those of organic carbon, elemental carbon, ash and hydrated sulphate. We have evaluated the performance of the extended model against available experimental data on engine power, fuel consumption and the composition-resolved emissions of PM. We have also compared the annually averaged emission values with those of the corresponding EMEP inventory, As example results, the geographical distributions of the emissions of PM and CO are presented for the marine regions of the Baltic Sea surrounding the Danish Straits.

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Abstract. Numerical models that combine weather forecasting and atmospheric chemistry are here referred to as chemical weather forecasting models. Eighteen operational chemical weather forecasting models on regional and continental scales in Europe are described and compared in this article. Topics discussed in this article include how weather forecasting and atmospheric chemistry models are integrated into chemical weather forecasting systems, how physical processes are incorporated into the models through parameterization schemes, how the model architecture affects the predicted variables, and how air chemistry and aerosol processes are formulated. In addition, we discuss sensitivity analysis and evaluation of the models, user operational requirements, such as model availability and documentation, and output availability and dissemination. In this manner, this article allows for the evaluation of the relative strengths and weaknesses of the various modelling systems and modelling approaches. Finally, this article highlights the most prominent gaps of knowledge for chemical weather forecasting models and suggests potential priorities for future research Published by Copernicus Publications on behalf of the European Geosciences Union. J. Kukkonen et al.: A review of operational, regional-scale, chemical weather forecasting models in Europedirections, for the following selected focus areas: emission inventories, the integration of numerical weather prediction and atmospheric chemical transport models, boundary conditions and nesting of models, data assimilation of the various chemical species, improved understanding and parameterization of physical processes, better evaluation of models against data and the construction of model ensembles.

Abstract. This paper investigates a potential of two remotely sensed wild-land fire characteristics: 4-µm Brightness Temperature Anomaly (TA) and Fire Radiative Power (FRP) for the needs of operational chemical transport modelling and short-term forecasting of atmospheric composition and air quality. The treatments of the TA and FRP data are presented and a methodology for evaluating the emission fluxes of primary aerosols (PM 2.5 and total PM) is described. The method does not include the complicated analysis of vegetation state, fuel load, burning efficiency and related factors, which are uncertain but inevitably involved in approaches based on burnt-area scars or similar products. The core of the current methodology is based on the empirical emission factors that are used to convert the observed temperature anomalies and fire radiative powers into emission fluxes. These factors have been derived from the analysis of several fire episodes in Europe (28.4-5.5.2006, 15.8-25.8.2006 and in August 2008. These episodes were characterised by: (i) well-identified FRP and TA values, and (ii) available groundbased observations of aerosol concentrations, and optical thickness for the regions where the contribution of the fire smoke to the concentrations of PM 2.5 was dominant, in comparison with those of other pollution sources. The emission factors were determined separately for the forested and grassland areas; in case of mixed-type land use, an intermediate scaling was assumed. Despite significant differences between the TA and FRP methodologies, an accurate nonlinear fitting was found between the predictions of these approaches. The agreement was comparatively weak only for small fires, for which the accuracy of both products is exCorrespondence to: M. Sofiev (mikhail.sofiev@fmi.fi) pected to be low. The applications of the Fire Assimilation System (FAS) in combination with the dispersion model SILAM showed that both the TA and FRP products are suitable for the evaluation of the emission fluxes from wild-land fires. The fire-originated concentrations of aerosols (PM 2.5 , PM 10 , sulphates and nitrates) and AOD, as predicted by the SILAM model were mainly within a factor of 2-3 compared with the observations. The main challenges of the FAS improvement include refining of the emission factors globally, determination of the types of fires (smouldering vs flaming), evaluation of the injection heights of the plumes, and predicting the temporal evolution of fires.

A birch pollen emission model is described and its main features are discussed. The development of the model is based on a double-threshold temperature sum model that describes the propagation of the flowering season and naturally links to the thermal time models to predict the onset and duration of flowering. For the flowering season, the emission model considers ambient humidity and precipitation rate, both of which suppress the pollen release, as well as wind speed and turbulence intensity, which promote it. These dependencies are qualitatively evaluated using the aerobiological observations. Reflecting the probabilistic character of the flowering of an individual tree in a population, the model introduces relaxation functions at the start and end of the season. The physical basis of the suggested birch pollen emission model is compared with another comprehensive emission module reported in literature. The emission model has been implemented in the SILAM dispersion modelling system, the results of which are evaluated in a companion paper.