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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.

Since the first International Cooperative for Aerosol Prediction (ICAP) multi‐model ensemble (MME) study, the number of ICAP global operational aerosol models has increased from five to nine. An update of the current ICAP status is provided, along with an evaluation of the performance of ICAP‐MME over 2012–2017, with a focus on June 2016–May 2017. Evaluated with ground‐based Aerosol Robotic Network (AERONET) aerosol optical depth (AOD) and data assimilation quality MODerate‐resolution Imaging Spectroradiometer (MODIS) retrieval products, the ICAP‐MME AOD consensus remains the overall top‐scoring and most consistent performer among all models in terms of root‐mean‐square error (RMSE), bias and correlation for total, fine‐ and coarse‐mode AODs as well as dust AOD; this is similar to the first ICAP‐MME study. Further, over the years, the performance of ICAP‐MME is relatively stable and reliable compared to more variability in the individual models. The extent to which the AOD forecast error of ICAP‐MME can be predicted is also examined. Leading predictors are found to be the consensus mean and spread. Regression models of absolute forecast errors were built for AOD forecasts of different lengths for potential applications. ICAP‐MME performance in terms of modal AOD RMSEs of the 21 regionally representative sites over 2012–2017 suggests a general tendency for model improvements in fine‐mode AOD, especially over Asia. No significant improvement in coarse‐mode AOD is found overall for this time period.

Abstract. 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 (PM2.5). 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 PM2.5 in summer was underestimated strongly by CMAQ and to some extent by EMEP/MSC-W. Observed PM2.5 in winter was underestimated by SILAM. In autumn all models were in better agreement with observed PM2.5. 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 PM2.5 levels in coastal land areas is in the range of 3.1 %–5.7 % for the three CTMs. Differences in ship-related PM2.5 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.

Background The analysis of mobile health (mHealth) data has generated innovative insights into improving allergic rhinitis control, but additive information is needed. A cross-sectional real-world observational study was undertaken in 17 European countries during and outside the estimated pollen season. The aim was to collect novel information including the phenotypic characteristics of the users. Methods The Allergy Diary–MASK-air–mobile phone app, freely available via Google Play and App, was used to collect the data of daily visual analogue scales (VASs) for overall allergic symptoms and medication use. Fluticasone Furoate (FF), Mometasone Furoate (MF), Azelastine Fluticasone Proprionate combination (MPAzeFlu) and eight oral H1-antihistamines were studied. Phenotypic characteristics were recorded at entry. The ARIA severity score was derived from entry data. This was an a priori planned analysis. Results 9037 users filled in 70,286 days of VAS in 2016, 2017 and 2018. The ARIA severity score was lower outside than during the pollen season. Severity was similar for all treatment groups during the pollen season, and lower in the MPAzeFlu group outside the pollen season. Days with MPAzeFlu had lower VAS levels and a higher frequency of monotherapy than the other treatments during the season. Outside the season, days with MPAzeFlu also had a higher frequency of monotherapy. The number of reported days was significantly higher with MPAzeFlu during and outside the season than with MF, FF or oral H1-antihistamines. Conclusions This study shows that the overall efficacy of treatments is similar during and outside the pollen season and indicates that medications are similarly effective during the year.