Through Arctic amplification, global climate change is projected to disproportionally affect high-latitude environments. Additionally, the geographical heterogeneity and complex terrain of mountains promote climate-driven ecological change on fine spatial scales. We used a high-resolution convection-permitting regional climate model (HCLIM) and a state-of-the-art dynamic vegetation model (LPJ-GUESS) to explore mid-twentieth century implications of continued global warming for reindeer herding, tourism and nature conservation in the mountainous, northern parts of Scandinavia. Several indicators relevant for stakeholders were investigated: length of snow season, crossings of zero temperature, rain-on-snow events, as well as tree and forest line shifts. Comparing results from the high-resolution (3 km) climate model with results from a coarser-scale (12 km) model commonly used for climate change assessments revealed that ecologically and societally significant patterns become apparent only at higher resolution. Large changes are projected among all investigated indicators for the present century, and we explore their societal implications.

This study illustrates how a temporally consistent deposition reanalysis can be used 1/ as input data to ecosystem impact assessments, 2/ to understand past trends, and 3/ for validation of decadal to century-scale model scenarios. We have constructed a multi-decadal (1983-2013) reanalysis of nitrogen deposition (NDEP) to northern Europe, including the Baltic Sea and the Scandinavian Mountains, using a combination of observations and modelling. We expanded the period with an operational annual reanalysis applying chemistry transport modelling, resulting in a fused dataset using the MATCH Sweden system for the period 1983-2021, and compared this to multi-century model scenarios of nitrogen deposition. Since the 1980s, NDEP has decreased until early 2010s in northern Europe including the Baltic Sea (by 32 %) and the Scandinavian Mountains (by 19 %). Present NDEP is on pair with the levels in the 1950s, after peaking in 1980-1990. We project continued decrease in oxidized NDEP until 2050, but still exceeding the pre-industrial levels. We also project an increase in reduced NDEP from present to mid-21st century, with stronger signal compared to previous estimates. This results in a weakening of the annual reduction of NDEP, stabilizing to the levels of the 1940s to 1950s by mid-21st century, resulting in approximately twice as high NDEP compared to pre-industrial times. The projected NDEP decrease will likely not be sufficient to avoid future effects on sensitive ecosystems. Thus, there is a need for continued efforts to further decrease nitrogen emissions to the atmosphere for protection of terrestrial and aquatic environments, not the least as ecosystems are under additional pressure of climate change and intensive management. The NDEP trends and levels in our model scenarios compare well to the reanalysis results (including fused observations).

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.

The Fennoscandian boreal and mountain regions harbour a wide range of vegetation types, from boreal forest to high alpine tundra and barren soils. The area is facing a rise in air temperature above the global average and changes in temperature and precipitation patterns. This is expected to alter the Fennoscandian vegetation composition and change the conditions for areal land use such as forestry, tourism and reindeer husbandry. In this study we used a unique high-resolution (3 km) climate scenario with considerable warming resulting from strongly increasing carbon dioxide emissions to investigate how climate change can alter the vegetation composition, biodiversity and availability of suitable reindeer forage. Using a dynamical vegetation model, including a new implementation of potential reindeer grazing, resulted in simulated vegetation maps of unprecedented high resolution for such a long time period and spatial extent. The results were evaluated at the local scale using vegetation inventories and for the whole area against satellite-based vegetation maps. A deeper analysis of vegetation shifts related to statistics of threatened species was performed in six “hotspot” areas containing records of rare and threatened species. In this high-emission scenario, the simulations show dramatic shifts in the vegetation composition, accelerating at the end of the century. Alarmingly, the results suggest the southern mountain alpine region in Sweden will be completely covered by forests at the end of the 21st century, making preservation of many rare and threatened species impossible. In the northern alpine regions, most vegetation types will persist but shift to higher elevations with reduced areal extent, endangering vulnerable species. Simulated potential for reindeer grazing indicates latitudinal differences, with higher potential in the south in the current climate. In the future these differences will diminish, as the potentials will increase in the north, especially for the summer grazing grounds. These combined results suggest significant shifts in vegetation composition over the present century for this scenario, with large implications for nature conservation, reindeer husbandry and forestry.

In the summer of 2018, Sweden experienced widespread wildfires, particularly in the region of Jämtland Härjedalen during the final weeks of July. We previously conducted an epidemiological study and investigated acute respiratory health effects in eight municipalities relation to the wildfire air pollution. In this study, we aimed to estimate the potential health impacts under less favorable conditions with different locations of the major fires. Our scenarios focused on the most intense plume from the 2018 wildfire episode affecting the largest municipality, which is the region’s only city. Combining modeled PM2.5 concentrations, gridded population data, and exposure–response functions, we assessed the relative increase in acute health effects. The cumulative population-weighted 24 h PM2.5 exposure during the nine highest-level days reached 207 μg/m3 days for 63,227 inhabitants. We observed a small number of excess cases, particularly in emergency unit visits for asthma, with 13 additional cases compared to the normal 12. Overall, our scenario-based health impact assessment indicates minor effects on the studied endpoints due to factors such as the relatively small population, limited exposure period, and moderate increase in exposure compared to similar assessments. Nonetheless, considering the expected rise in fire potential due to global warming and the long-range transport of wildfire smoke, raising awareness of the potential health risks in this region is important.

This dataset contains data published on the webtool of the BioDiv-Support project:https://biodivsupport-tst.smhi.se/ The project involves climate, air pollution and vegetation model projections for assessing ecosystem changes, biodiversity and adaptation, focusing on pristine mountain regions.v1.0 includes data on the Scandinavian Mountains. For detailed information, please see the website.

Associations between the annual stem basal area increment growth and soil moisture, nitrogen deposition, ground level ozone exposure, air temperatures and the timing of the start of the growing season have been investigated for a twenty four-year period, 1990-2013, based on tree-ring width measurements from seventeen monitoring sites with Norway spruce (Picea abies) forests in southern Sweden. The stem growth-environment associations were analyzed using a fixed effect regression model, with annual stem basal area increment (BAI) as the dependent variable and annual values for a soil moisture index, ozone exposure estimated as AOT30, bulk deposition of nitrogen, summed air temperatures above a threshold and the timing of the start of the growing season as explanatory variables. The statistical analysis was made with and without taking clustering of the sampled trees into account, i.e. that several different tree observations were made at the same monitoring site. The annual number of days with soil moisture below a threshold was the only explanatory variable that could be demonstrated to be negatively associated with changes in BAI, regardless of statistical approach. Positive associations between temperature sums as well as nitrogen deposition with changes in BAI were indicated by low p values using standard p-values, but not when clustering was taken into consideration. Associations between ozone exposure as well as the start date of the growing season with changes in BAI could not be demonstrated since the estimated p values were high regardless of statistical approach. The results show that soil water deficit may considerably limit forest growth in northern European forests.

Abstract. The Fennoscandian boreal and mountain regions harbour a wide range of vegetation types, from boreal forest to high alpine tundra and barren soils. The area is facing a rise in air temperature above the global average and changes in temperature and precipitation patterns. This is expected to alter the Fennoscandian vegetation com-position and change the conditions for areal land-use such as forestry, tourism and reindeer husbandry. In this study we used a unique high-resolution (3 km) climate scenario with considerable warming resulting from strongly increasing carbon dioxide emissions to investigate how climate change can alter the vegetation composition, biodiversity and availability of suitable reindeer forage. Using a dynamical vegetation model, including a new implementation of potential reindeer grazing, resulted in simulated vegetation maps of unprecedented high resolution for such a long time period and spatial extent. The results were evaluated at the local scale using vegetation inventories and for the whole area against satellite-based vegetation maps. A deeper analysis of vegetation shifts related to statistics of threatened species was performed in six “hotspot” areas containing records of rare and threatened species. The simulations show dramatic shifts in the vegetation composition, accelerating at the end of the century. Alarmingly, the results suggest the southern mountain alpine region in Sweden will be completely covered by forests at the end of the 21st century, making preservation of many rare and threatened species impossible. In the northern alpine regions, most vegetation types will persist but shift to higher elevations with reduced areal extent, endangering vulnerable species. Simulated potential for reindeer grazing indicates latitudinal differences, where the current higher potentials in the south will diminish, while future potentials will increase in the north, especially for the summer grazing grounds. These combined results suggest significant shifts in vegetation composition over the present century for this scenario, with large implications for nature conservation, reindeer husbandry and forestry.

Page S1.Maps of hotspots 2 S2.LPJ-Guess parameters tuned for the IBS plant functional type 3 S3.Description of the reindeer grazing, browsing and trampling implementation 4-5 S4.Climate-change signal in the climate scenario 6 S5.Description of conversion of PFT LAI to vegetation classes 7-8 S6.Validation results 9-11 S7.Confusion matrixes for simulated and satellite-based vegetation classes: a. Abisko 12 b.Vindeln 13 c.Helags 14 d.Fulu 15 e.Muddus 16 f.Björnlandet 17 S8.Simulated potential reindeer consumption in Swedish reindeer-herding communities 18-19

Individual high-Alpine ice cores have been proven to contain a well-preserved history of past anthropogenic air pollution in western Europe. The question of how representative one ice core is with respect to the reconstruction of atmospheric composition in the source region has not been addressed so far. Here, we present the first study systematically comparing longer-term ice-core records (1750-2015 CE) of various anthropogenic compounds, such as major inorganic aerosol constituents (NH C (4), NO (3), SO42), black carbon (BC), and trace species (Cd, F, Pb). Depending on the data availability for the different air pollutants, up to five ice cores from four high-Alpine sites located in the European Alps analysed by different laboratories were considered. Whereas absolute concentration levels can partly differ depending on the prevailing seasonal distribution of accumulated precipitation, all seven investigated anthropogenic compounds are in excellent agreement between the various sites for their respective, species-dependent longer-term concentration trends. This is related to common source regions of air pollution impacting the four sites less than 100 km away including western European countries surrounding the Alps. For individual compounds, the Alpine ice-core composites developed in this study allowed us to precisely time the onset of pollution caused by industrialization in western Europe. Extensive emissions from coal combustion and agriculture lead to an exceeding of pre-industrial (1750-1850) concentration levels already at the end of the 19th century for BC, Pb, exSO(4)(2) (non-dust, non-sea salt SO42), and NH C (4), respectively. However, Cd, F, and NO (3) concentrations started surpassing preindustrial values only in the 20th century, predominantly due to pollution from zinc and aluminium smelters and traffic. The observed maxima of BC, Cd, F, Pb, and exSO(4)(2) concentrations in the 20th century and a significant decline afterwards clearly reveal the efficiency of air pollution control measures such as the desulfurization of coal, the introduction of filters and scrubbers in power plants and metal smelters, and the ban of leaded gasoline improving the air quality in western Europe. In contrast, NO (3) and NH C 4 concentration records show levels in the beginning of the 21th century which are unprecedented in the context of the past 250 years, indicating that the introduced abatement measures to reduce these pollutants were insufficient to have a major effect at high altitudes in western Europe. Only four ice-core composite records (BC, F, Pb, exSO(4)(2)) of the seven investigated pollutants correspond well with modelled trends, suggesting inaccuracies of the emission estimates or an incomplete rep-resentation of chemical reaction mechanisms in the models for the other pollutants. Our results demonstrate that individual ice-core records from different sites in the European Alps generally provide a spatially representative signal of anthropogenic air pollution trends in western European countries.

This study presents a comprehensive evaluation of the combination of the regional scale chemistry-transport model DEHM (Danish Eulerian Hemispheric Model) and the Gaussian plume-in-grid model UBMv10 (Urban Background Model). The focus of the study was centred around the following research question: the combination of an Eulerian regional scale approach and a Gaussian high-resolution/local scale approach improves the performance from evaluation with measurements compared to the Eulerian regional scale approach alone. We also investigated the research question that the integrated Eulerian/Gaussian approach has a similar performance as Eulerian models set up with the same high spatial resolution. The DEHM/UBM model has been run for a domain covering Denmark, Finland, Norway and Sweden with a 1 km x 1 km spatial resolution, producing hourly concentration estimates for four decades, 1979-2018. The results were evaluated against rural and urban background measurements in the four countries and the performance of the DEHM/UBM model was compared to the performance of the DEHM model based on a similar evaluation. The comparison showed that the DEHM/UBM model, in general, performs similar to the DEHM model, however, DEHM/UBM captures the interannual variability better in most cases. The DEHM/UBM model results for 2015 were also compared with corresponding high-resolution results from the chemistry-transport models SILAM (System for Integrated modeLling of Atmospheric coMposition) and MATCH (Multi-scale Atmospheric Transport and CHemistry model) for the four Nordic capitals; Copenhagen, Helsinki, Oslo and Stockholm. This model comparison was carried out to evaluate and compare the performance of the relatively simple, yet computationally fast approach of the DEHM/UBM model setup to the more time-consuming approaches of applied regional scale models on very high-resolution. The DEHM/UBM model performed similarly to SILAM and MATCH for most components, however, the 3D models performed better with respect to capturing the differences between rural and urban settings for the four capitals.

Abstract. The Eurodelta-Trends multi-model experiment, aimed to assess the efficiency of emission mitigation measures in improving air quality in Europe during 1990–2010, was designed to answer a series of questions regarding European pollution trends. i.e. were there significant trends detected by observations? do the models manage to reproduce observed trends? how close is the agreement between the models and how large are the deviations from observations? In this paper, we address these issues with respect to PM pollution. An in-depth trend analysis has been performed for PM10 and PM2.5 for the period of 2000–2010, based on results from six chemical transport models and observational data from the EMEP (Cooperative Programme for Monitoring and Evaluation of the Long-range Transmission of Air Pollutants in Europe) monitoring network. Given harmonization of set up and main input data, the differences in model results should mainly result from differences in the process formulations within the models themselves, and the spread in the models simulated trends could be regarded as an indicator for modelling uncertainty. The model ensemble simulations indicate overall decreasing trends in PM10 and PM2.5, with reduction by between 2 and 6 μg m−3 m−3 (or between 10 and 30 %) from 2000 to 2010. Compared to PM2.5, relative PM10 trends are weaker due to large inter-annual variability of natural coarse PM within the former. The changes in the concentrations of PM individual components are in general consistent with emission reductions. There is a reasonable agreement in PM trends estimated by the individual models, with the inter-model variability below 30–40 % over most of Europe, increasing to 50–60 % in northern and eastern parts of EDT domain. Averaged over measurement sites (26 for PM10 and 13 for PM2.5), the mean ensemble simulated trends are −0.24 and −0.22 μg m−3 year−1 for PM10 and PM2.5, which are somewhat weaker than the observed trends of −0.35 and −0.40 μg m−3 year−1, respectively, partly due to models underestimation of PM concentrations. The correspondence is better in relative PM10 and PM2.5 trends, which are −1.7 and −2.0 % year−1 from the model ensemble and −2.1 and −2.9 % year−1 from the observations, respectively. The observations identify significant trends for PM10 at 56 % of the sites and for PM2.5 at 36 % of the sites, which is somewhat less that the fractions of significant modelled trends. Further, we find somewhat smaller spatial variability of modelled PM trends with respect to the observed ones across Europe and also within individual countries. The strongest decreasing PM trends and the largest number of sites with significant trends is found for the summer season, according to both the model ensemble and observations. The winter PM trends are very weak and mostly insignificant. One important reason for that is the very modest reductions and even increases in the emissions of primary PM from residential heating in winter. It should be kept in mind that all findings regarding modeled versus observed PM trends are limited the regions where the sites are located. The analysis reveals a considerable variability of the role of the individual aerosols in PM10 trends across European countries. The multi-model simulations, supported by available observations, point to decreases in SO4−2 concentrations playing an overall dominant role. Also, we see relatively large contributions of the trends of NH4+ and NO3− to PM10 decreasing trends in Germany, Denmark, Poland and the Po Valley, while the reductions of primary PM emissions appears to be a dominant factor in bringing down PM10 in France, Norway, Portugal, Greece and parts of the UK and Russia. Further discussions are given with respect to emission uncertainties and the effect of inter-annual meteorological variability on the trend analysis.

Earth system and environmental impact studies need high quality and up-to-date estimates of atmospheric deposition. This study demonstrates the methodological benefits of multimodel ensemble and measurement-model fusion mapping approaches for atmospheric deposition focusing on 2010, a year for which several studies were conducted. Global model-only deposition assessment can be further improved by integrating new model-measurement techniques, including expanded capabilities of satellite observations of atmospheric composition. We identify research and implementation priorities for timely estimates of deposition globally as implemented by the World Meteorological Organization.

This study presents the evaluation of the high-resolution air pollution model UBMv10, which has been set-up for a 2,900,000 km2 domain covering Norway, Sweden, Finland and Denmark with a 1 km x 1 km resolution and run for the time period 1979-2018. The UBMv10 is coupled to a long-range transport-chemistry model, DEHM, for boundary conditions. High-resolution emission data input and measurements of urban and rural air pollution concentrations have been obtained within the NordicWelfAir project from the four countries, in order to provide input and basis for evaluation of the UBM model. In the NordicWelfAir project, the modelled hourly mean concentrations of air pollutants for the 40 year time period on this high resolution are applied in various epidemiological studies of the link between air pollution and health effects. The model results represent concentrations at the rural and urban background local scale level which in this study are evaluated for the components NO2, O3 and PM2.5, which are the most important components to address when studying health effects of air pollution. The simplicity of the model makes it possible to perform model runs for a combination of large domains with high resolution and long time periods that is currently very difficult to obtain with more comprehensive Eulerian high-resolution models, which take much longer time to run, since they are limited by the Courant–Friedrichs–Lewy (CFL) stability criteria. When studying the long-term effects of air pollution components, e.g. with the home address of individuals in a cohort as proxy, these high-resolution model runs are required. The evaluation is part of a study with the aim to investigate, how well the UBM model with its relatively simple description of atmospheric dispersion and chemistry captures the temporal and spatial variations in the four Nordic countries. In general, the model performs relatively well for describing the temporal variations with correlation coefficients around 0.5-0.8. The model has a tendency to overestimate NO2 levels with a few µg for all four countries, and overestimate PM2.5 with for Norway and Sweden with 3-5 µg across all stations. The coupled model setup will be presented together with examples of 40 years of high-resolution model results for the four Nordic countries as well as the results of the model evaluation against measurements in the domain.

During the summer of 2018 Sweden experienced a high occurrence of wildfires, most intense in the low-densely populated Jämtland Härjedalen region. The aim of this study was to investigate any short-term respiratory health effects due to deteriorated air quality generated by the smoke from wildfires. For each municipality in the region Jämtland Härjedalen, daily population-weighted concentrations of fine particulate matter (PM2.5) were calculated through the application of the MATCH chemistry transport model. Modelled levels of PM2.5 were obtained for two summer periods (2017, 2018). Potential health effects of wildfire related levels of PM2.5 were examined by studying daily health care contacts concerning respiratory problems in each municipality in a quasi-Poisson regression model, adjusting for long-term trends, weekday patterns and weather conditions. In the municipality most exposed to wildfire smoke, having 9 days with daily maximum 1-h mean of PM2.5 > 20 μg/m3, smoke days resulted in a significant increase in daily asthma visits the same and two following days (relative risk (RR) = 2.64, 95% confidence interval (CI): 1.28–5.47). Meta-estimates for all eight municipalities revealed statistically significant increase in asthma visits (RR = 1.68, 95% CI: 1.09–2.57) and also when grouping all disorders of the lower airways (RR = 1.40, 95% CI: 1.01–1.92).

Biodiversity includes any type of living variation, from the ecosystem level to genetic variation within organisms. The greatest threats to biodiversity is climate change, destruction of habitats and other human activities. High-altitude mountain regions are pristine environments, with historically small impacts from air pollution, but at risk of being disproportionately impacted by climate change. We focus on three mountainous regions: the Scandinavian Mountains, the Guadarrama Mountains in Spain, and the Pyrenees in France, Andorra and Spain. We study the impact of drivers of change of biodiversity such as future climate change, increased incidences of wild fires, emissions from new shipping routes in the Arctic as ice sheets are melting, human impacts on land use and management practices (such as reindeer grazing) and air pollution.We simulate future climate change using WRF and a convective permitting climate model, HARMONIE-Climate, with a spatial resolution of 3km. The high resolution strongly improves the representation of precipitation compared to coarser scale simulations (Lind et al., 2020). We use these simulations to develop future scenarios of air pollution load, using two well established chemistry transport models (MATCH and CHIMERE; Marécal et al., 2015). These climate and air pollution scenarios are subsequently used, together with management scenarios, to develop scenarios for biodiversity and ecosystem services. These scenarios are developed applying a process-based dynamic vegetation and biogeochemistry model, LPJ-GUESS (Smith et al., 2014).The scenarios, representing mid-21st century, will be made available through a web-based planning tool, where local stakeholders in each region can explore the project results to understand how scenarios of climate change, air pollution and policy development will affect these ecosystems. Local stakeholders are involved throughout the project, such as reindeer herder communities, regional county boards and national authorities, and in a time of changing climate and a global pandemic we have learned the necessity for flexibility in such interactions.ReferencesLind et al. 2020., Climate Dynamics 55, 1893-1912.Marécal et al., 2015. Geosci. Mod. Dev. 8, 2777-2813.Smith et al. 2014 Biogeosciences 11, 2027-2054.

International initiatives have successfully brought down the emissions, and hence also the related negative impacts on environment and human health, from shipping in Emission Control Areas (ECAs). However, the question remains as to whether increased shipping in the future will counteract these emission reductions. The overall goal of this study is to provide an up-to-date view on future ship emissions and provide a holistic view on atmospheric pollutants and their contribution to air quality in the Nordic (and Arctic) area. The first step has been to set up new and detailed scenarios for the potential developments in global shipping emissions, including different regulations and new routes in the Arctic. The scenarios include a Baseline scenario and two additional SOx Emission Control Areas (SE-CAs) and heavy fuel oil (HFO) ban scenarios. All three scenarios are calculated in two variants involving Business-As-Usual (BAU) and High-Growth (HiG) traffic scenarios. Additionally a Polar route scenario is included with new ship traffic routes in the future Arctic with less sea ice. This has been combined with existing Current Legislation scenarios for the land-based emissions (ECLIPSE V5a) and used as input for two Nordic chemistry transport models (DEHM and MATCH). Thereby, the current (2015) and future (2030, 2050) air pollution levels and the contribution from shipping have been simulated for the Nordic and Arctic areas. Population exposure and the number of premature deaths attributable to air pollution in the Nordic area have thereafter been assessed by using the health assessment model EVA (Economic Valuation of Air pollution). It is estimated that within the Nordic region approximately 9900 persons died prematurely due to air pollution in 2015 (corresponding to approximately 37 premature deaths for every 100 000 inhabitants). When including the projected development in both shipping and land-based emissions, this number is estimated to decrease to approximately 7900 in 2050. Shipping alone is associated with about 850 premature deaths during present day conditions (as a mean over the two models), decreasing to approximately 600 cases in the 2050 BAU scenario. Introducing a HFO ban has the potential to lower the number of cases associated with emissions from shipping to approximately 550 in 2050, while the SECA scenario has a smaller impact. The "worst-case" scenario of no additional regulation of shipping emissions combined with a high growth in the shipping traffic will, on the other hand, lead to a small increase in the relative impact of shipping, and the number of premature deaths related to shipping is in that scenario projected to be around 900 in 2050. This scenario also leads to increased deposition of nitrogen and black carbon in the Arctic, with potential impacts on environment and climate.

Preterm birth is the largest contributor to neonatal mortality globally and it is also associated with several adverse health outcomes. Recent studies have found an association between maternal exposure to air pollution and an increased risk for preterm birth. As a constituent of air pollution, ozone is a highly reactive molecule with several negative health effects when present near earth’s surface. This health impact assessment aims to estimate the proportion of preterm births—in current and future situations—attributable to maternal ozone exposure in 30 European countries (EU30). A literature search was performed using relevant keywords, followed by meta-analysis with STATA software in which five studies investigating exposure-response relationship of interest were included. The attributable proportion, and number of cases, was modelled with the software AirQ+ against current and future European ozone concentrations. According to our meta-analysis, the relative risk for giving birth preterm was calculated to 1.027 (95% CI 1.009–1.046) per 10 μ g m −3 increase in ozone concentration. This rendered 7.1% (95% CI 2.5–11.7) of preterm births attributable to maternal ozone exposure to in EU30 during 2010, which is equal to approximately 27 900 cases. By 2050, the projected decrease in ozone precursor emissions rendered an estimated 30% decrease of ozone attributable preterm births. Not taking emission change into account, due to climate change the ozone-related preterm birth burden might slightly increase by 2050 in Central and Southern Europe, and decrease in Eastern and Northern Europe. In summation, these numbers make a substantial impact on public health.

As part of the EPITOME project, we have setup global shipping emission scenarios. They are based on a combination of the global CO2 ship emission inventory for 2015 produced with the Ship Traffic Emissions Assessment Model (STEAM) (Johansson et al., 2017) and Arctic fuel consumption and emission scenarios calculated with the DCE ship emission model (Winther et al., 2017). The scenarios include a Baseline scenario, a SOx Emission Control Area (SECA) and a heavy fuel oil (HFO) ban scenario. The Baseline scenario is calculated in two variants involving Business As Usual (BAU) and High Growth (HiG) traffic growths. The SECA and HFO ban scenarios are given with the BAU traffic development. Additionally a Polar route scenario is included, with new (diversion) ship traffic routes in the future Arctic with less sea ice. The applied traffic growths and the polar routes are Corbett et al. (2010). The emissions are monthly on a spatial resolution of 0.1º×0.1º. Base year is 2015 and the scenarios are for 2050. A scientific paper providing details on the methodology behind these data will be submitted to ACPD (Geels et al, submitted). In this paper we apply the data to assess the contribution from shipping emissions to air pollution in the Nordic and Arctic area and the potential benefits of the mitigation options included in the shipping emission scenarios. This paper should be referenced if the data is used. The data are given as netcdf files for a number of components. The emission related to the diversion routes is given as a separate field and can be added the other field.