Background The association between socioeconomic status (SES) and environmental burden is context-dependent. Those with low SES may be more likely to live near major roads and industries where environmental exposures are high but may also be more likely to live further away from city centers. The aim of this study was to investigate the association between SES and environmental burden in Sweden. Methods The Swedish CArdioPulmonary bioImage Study (SCAPIS) cohort recruited participants from six Swedish cities during 2013-2018. Residential environmental exposures (particulate matter <2.5 m [PM2.5], road traffic noise, and lack of greenspace) and neighborhood-level SES factors (proportions with low-income, low education, unemployment, rental units, foreign born) were assessed from participants' addresses in 2018. Individual-level SES factors (financial buffer, education, occupation, type of living, foreign born) were obtained from a questionnaire and neighborhood data from Statistics Sweden. Linear regression models were used to analyze the link between environmental exposures and SES factors. Correlations between SES factors were analyzed using Cram & eacute;r's V and Spearman rank correlations. Results The study included 23 320 SCAPIS participants in 1939 neighborhoods. The explanatory power of SES factors differed substantially between factors and cities. A model with all ten SES factors could account for 25-88 %, 36-60 %, and 49-81 % of the spatial variance in PM2.5, noise, and lack of greenspace respectively. Neighborhoods with more low-income earners, rental units and foreign born had more environmental burden. Neighborhoods with more inhabitants with low education and unemployment had less environmental burden. Associations were generally non-linear. Individual-level SES factors were not associated with environmental burdens after adjusting for neighborhood SES factors. Individual and neighborhood SES were weakly correlated. Conclusion Neighborhood SES factors accounted for a large proportion of the variance in environmental burdens, whereas individual SES factors did not. The relationship between SES and environmental burden differed greatly between indicators and cities.

Ambient air pollution remains the major environmental cause of disease. Accurate assessment of population exposure and small-scale spatial exposure variations over long time periods is essential for epidemiological studies. We estimated annual exposure to fine and coarse particulate matter (PM 2.5 , PM 10 ), and nitrogen oxides (NO x , NO 2 ) with high spatial resolution to examine time trends 2000‒2018, compliance with the WHO Air Quality Guidelines, and assess the health impact. The modelling area covered six metropolitan areas in Sweden with a combined population of 5.5 million. Long-range transported air pollutants were modelled using a chemical transport model with bias correction, and locally emitted air pollutants using source-specific Gaussian-type dispersion models at resolutions up to 50 × 50 m. The modelled concentrations were validated using quality-controlled monitoring data. Lastly, we estimated the reduction in mortality associated with the decrease in population exposure. The validity of modelled air pollutant concentrations was good (R 2 for PM 2.5 0.84, PM 10 0.61, and NO x 0.87). Air pollution exposure decreased substantially, from a population weighted mean exposure to PM 2.5 of 12.2 µg m −3 in 2000 to 5.4 µg m −3 in 2018. We estimated that the decreased exposure was associated with a reduction of 2719 (95% CI 2046–3055) premature deaths annually. However, in 2018, 65%, 8%, and 42% of residents in the modelled areas were still exposed to PM 2.5 , PM 10 , or NO 2 levels, respectively, that exceeded the current WHO Air Quality Guidelines for annual average exposure. This emphasises the potential public health benefits of reductions in air pollution emissions.

BACKGROUND AND AIM: The Swedish CArdioPulmonary bioImage Study, SCAPIS, is a nationwide population-based cohort for the study of cardiovascular and pulmonary disease. A total of 31,265 men and women aged 50-64 years old were recruited and investigated including detailed imaging of the cardiovascular and pulmonary systems. The database currently covers over 1,300 different variables and is growing. METHODS: We modelled yearly PM2.5 levels in the six SCAPIS regions, including major source types, traffic exhaust, road wear and resuspension, residential heating, shipping, with a spatial resolution of 50 x 50 m and assigned participants exposure 2000, 2011, and 2018. These areas cover over 40% of the total population in Sweden. RESULTS: The time trend within the cohort showed a strong decrease in Long Range Transported (LRT) pollutants for the 2000s for all study regions, but for Stockholm Uppsala and Umeå the LRT exposure levels levelled out during the 2010s. There was a decreasing gradient of LRT concentrations from the highest levels in the south to the lowest levels in the north. The relative importance of the different local sources, and their respective temporal trends, were site dependent. Malmö was strongly influenced by the closeness to Copenhagen, especially in the beginning of the study period. Gothenburg had the strongest influence from shipping, and the relative importance of residential heating was strongest in Umeå in the north. Another general trend was that traffic exhaust particles decreased over time, while the particle concentrations from traffic road wear and resuspension instead increased, illustrating the tail pipe emission reduction and the traffic increase. CONCLUSIONS: Exposure to air pollution in Sweden have decreased in the last two decades, but the pattern varies for the different regions and sources.

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.

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.

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.

Traffic and residential wood combustion (rwc) constitute the two dominating local sources to fine particulate matter PM2.5 concentration levels in Sweden. In order to meet the authorities’ requirements of air quality assessments, a national modelling system SIMAIR has been developed. The system is based on the commercial Airviro air quality management software, a three tier client/server/web system which includes modules for measurement data collection, emission databases and dispersion models with very high performance in terms of data access and model execution. The technical characteristics of Airviro databases and models have facilitated web based national air quality systems, of which some examples are given. The present Airviro/SIMAIR application had the objective to assess the impact of rwc in three urbanized areas in northern Sweden. The Airviro Scenario module was used to determine exposure and health impact of the rwc contribution. The estimated mortality due to PM2.5 concentrations from residential wood combustion is about 4 persons/year, which corresponds to approximately 0.4

Environment Climate Data Sweden (ECDS) is a new Swedish research infrastructure, furthering the reuse of scientific data in the domains of environment and climate. ECDS consists of a technical infrastructure and a service organization, supporting the management, exchange, and re-use of scientific data. The technical components of ECDS include a portal and an underlying data catalogue with information on datasets. The datasets are described using a metadata profile compliant with international standards. The datasets accessible through ECDS can be hosted by universities, institutes, or research groups or at the new Swedish federated data storage facility Swestore of the Swedish National Infrastructure for Computing (SNIC).

The PM10 concentrations exceed the EU limit values in almost all countries in Europe. Especially, in many Nordic cities, non-exhaust particle emissions are the main reason for high PM10 levels along densely trafficked roads. This is connected to the use of studded tyres and winter time road traction maintenance, e.g. salting and sanding. The ultimate aim of the project has been to develop a process based emission model, that can be applied in any city without site specific empirical factors, for management and evaluation of abatement strategies and that is able to describe the (non-exhaust) emissions on an hourly or at least daily basis with satisfactory accuracy. The model is built upon existing road dust emission models, combined with field and laboratory measurements. The major features of the model are:Road dust and salt loading is calculated based on a mass balance equationProduction of road dust, and subsequent emissions, are based on the total wear of road, brakes and tyresMaintenance activities (e.g. salting, sanding, cleaning, ploughing) contribute to the mass balance as well as processes such as drainage and splash/sprayRetention of road surface dust is dependent on the surface moisture contentThe road surface moisture is calculated based on a mass balance equation for surface water and iceEvaporation is based on energy balance modelling of the road surfaceMaintenance activities (e.g. cleaning, ploughing, salt solutions) and processes (e.g. drainage, splash/ spray) are included in the moisture mass balanceThe impact of salting on both dust retention and melt temperature is considered

Non-exhaust traffic induced emissions are a major source of particle mass in most European countries. This is particularly important in Nordic and Alpine countries where winter time road traction maintenance occurs, e.g. salting and sanding, and where studded tyres are used. Modelling these emissions is a challenging task as they are sensitive to environmental factors such as road surface moisture as well as road maintenance activities (salting and sanding) and tyre and vehicle types. The ability to model these emissions is desirable as this provides the potential for more effective road management, improved assessment of mitigation strategies for reducing emissions and can help quantify the impact of salting and sanding activities. These are all important applications relevant to the European AQ Directive. The Nordic based project NORTRIP is building upon existing road dust emission models, combined with field and laboratory measurements, to develop a more comprehensive and generalised process based model description of the non-exhaust emissions, with emphasis on the contribution of road wear, salt and sand to the emissions. In this paper we present the current status of the modelling, briefly describing the processes and their parameterisations. The performance of the model is illustrated using two example applications from Norway and Sweden and future developments are discussed.

The tropospheric aerosol is a complex constituent of the atmosphere that has impacts on health and the climate. This thesis presents five different studies from Tanzania, Southeast Asia and Europe dealing with urban measurements of particle mass and elemental composition, regional scale modelling of ozone and particle mass of inorganic aerosols and development of modules for sea salt emissions and size resolved aerosol particles with aerosol dynamical mechanisms implemented in a regional scale chemistry and transport model (CTM). The first research task, which was measurements in Dar es Salaam, Tanzania, uses information on elemental composition and temporal behaviour to find sources of particulate mass with a simple statistical model. The second research task used available monitored species in Asia to set up and evaluate a regional chemical transport model developed and used for European conditions. This model was then compared to other models in the Asian region. The regional scale model was also set up for Europe to test new parameterisations of sea salt emissions and size distributed aerosols. A conclusion drawn from measurements in Dar es Salaam is that there is an enhanced concentration of small particles of anthropogenic origin in the city. In Southeast Asia, the evaluation of the CTM with respect to ozone was found to be difficult as a result of unrepresentative monitoring data. The study does indicate that the model performance is representative, but more comparisons should be made before concluding that the model is as valid as it is in Europe. An ensemble of models set up for East and Southeast Asia was able to reproduce the temporal variation for monitored particulate nitrate and sulphate. For simulations of the annual mean of nitrate, most models underestimated the measured values. All models in the ensemble either underestimated or overestimated total ammonium at five different stations, indicating that the emission inventory used by all the models considered here might be the reason for the bias of models to measurements. The new sea salt emission module overestimated the value of monitored sodium, but the correlation was good. Introducing aerosol dynamics in the model made the bias smaller, but also the correlation decreased. An aerosol dynamics module was successfully implemented in a regional scale CTM and can produce size distributed number and mass of several species. The introduction of aerosol dynamics did not degrade the performance of the model with respect to total inorganic particle mass.

Eight regional Eulerian chemical transport models (CTMs) are compared with each other and with an extensive set of observations including ground-level concentrations from EANET, ozone soundings from JMA and vertical profiles from the TRACE-P experiment to evaluate the models' abilities in simulating O3 and relevant species (SO2, NO, NO2, HNO3 and PAN) in the troposphere of East Asia and to look for similarities and differences among model performances. Statistical analysis is conducted to help estimate the consistency and discrepancy between model simulation and observation in terms of various species, seasons, locations, as well as altitude ranges. In general, all models show a good skill of simulating SO2 for both ground level and the lower troposphere, although two of the eight models systematically overpredict SO2 concentration. The model skills for O3 vary largely with region and season. For ground-level O3, model results are best correlated with observations in July 2001. Comparing with O3 soundings measured in the afternoon reveals the best consistency among models in March 2001 and the largest disparity in O3 magnitude in July 2001, although most models produce the best correlation in July as well. In terms of the statistics for the four flights of TRACE-P experiment, most models appear to be able to accurately capture the variability in the lower troposphere. The model performances for NOx are relatively poor, with lower correlation and with almost all models tending to underpredict NOx levels, due to larger uncertainties in either emission estimates or complex chemical mechanism represented. All models exhibit larger RMSE at altitudes <2 km than 2–5.5 km, mainly due to a consistent tendency of these models towards underprediction of the magnitude of intense plumes that often originate from near surface. Relatively lower correlation at altitudes 2–5.5 km may be attributed to the models' limitation in representing convection or potential chemical processes. Most of the key features in species distribution have been consistently reproduced by the participating models, such as the O3 enhancement in the western Pacific Ocean in March and in northeast Asia in July, respectively, although the absolute model values may differ considerably from each other. Large differences are found among models in the southern parts of the domain for all the four periods, including southern China and northern parts of some Southeast Asia countries where the behaviors of chemical components and the ability of these models are still not clearly known because of a lack of observational databases.