Deriving a parameterisation of ammonia emissions for use in chemistry-transport models (CTMs) is a complex problem as the emission varies locally as a result of local climate and local agricultural management. In current CTMs such factors are generally not taken into account. This paper demonstrates how local climate and local management can be accounted for in CTMs by applying a modular approach for deriving data as input to a dynamic ammonia emission model for Europe. Default data are obtained from information in the RAINS system, and it is demonstrated how this dynamic emission model based on these input data improves the NH₃ calculations in a CTM model when the results are compared with calculations obtained by traditional methods in emission handling. It is also shown how input data can be modified over a specific target region resulting in even further improvement in performance over this domain. The model code and the obtained default values for the modelling experiments are available as supplementary information to this article for use by the modelling community on similar terms as the EMEP CTM model: the GPL licencse v3.

We have developed an integrated model system, EVA (Economic Valuation of Air pollution), based on the impact-pathway chain, to assess the health-related economic externalities of air pollution resulting from specific emission sources or sectors, which can be used to support policy-making with respect to emission control. Central for the system is a newly developed tagging method capable of calculating the contribution from a specific emission source or sector to the overall air pollution levels, taking into account the non-linear atmospheric chemistry. The main objective of this work is to identify the anthropogenic emission sources in Europe and Denmark that contribute the most to human health impacts. In this study, we applied the EVA system to Europe and Denmark, with a detailed analysis of health-related external costs from the ten major emission sectors and their relative contributions. The paper contains a thorough description of the EVA system, the main results from the assessment of the main contributors and a discussion of the most important atmospheric chemical reactions relevant for interpreting the results. The main conclusion from the analysis is that the major contributors to health-related external costs are major power production, agriculture, road traffic, and non-industrial domestic combustion, including wood combustion. We conclude that when regulating the emissions of ammonia from the agricultural sector, both the impacts on nature and on human health should be taken into account. This study confirms that air pollution constitutes a serious problem for human health and that the related external costs are considerable. The results in this work emphasize the importance of defining the right questions in the decision-making process. The results from assessing the impacts from each emission sector depend clearly on the assumption that the other emission sectors are not changed, especially emissions changing concentrations of atmospheric OH and therefore lifetimes of other chemical species.

An integrated model system, EVA (Economic Valuation of Air pollution), based on the impact-pathway chain has been developed to assess the health-related economic externalities of air pollution resulting from specific emission sources or sectors. The model system can be used to support policy-making with respect to emission control. In this study, we apply the EVA system to Europe, and perform a more detailed assessment of past, present, and future health-cost externalities of the total air pollution levels in Europe (including both natural and anthropogenic sources), represented by the years 2000, 2007, 2011, and 2020. We also assess the contribution to the health-related external costs from international ship traffic with special attention to the international ship traffic in the Baltic and North seas, since special regulatory actions on sulfur emissions, called SECA (sulfur emission control area), have been introduced in these areas. We conclude that, despite efficient regulatory actions in Europe in recent decades, air pollution still constitutes a serious problem for human health. Hence the related external costs are considerable. The total health-related external costs for the whole of Europe are estimated at 803 bn euros yr⁻¹ for the year 2000, decreasing to 537 bn euros yr⁻¹ in the year 2020. We estimate the total number of premature deaths in Europe in the year 2000 due to air pollution to be around 680 000 yr⁻¹, decreasing to approximately 450 000 in the year 2020. The contribution from international ship traffic in the Northern Hemisphere was estimated to 7% of the total health-related external costs in Europe in the year 2000, increasing to 12% in the year 2020. In contrast, the contribution from international ship traffic in the Baltic Sea and the North Sea decreases 36% due to the regulatory efforts of reducing sulfur emissions from ship traffic in SECA. Introducing this regulatory instrument for all international ship traffic in the Northern Hemisphere, or at least in areas close to Europe, would have a significant positive impact on human health in Europe.

Ambient air pollution has been linked to stroke, but few studies have examined in detail stroke subtypes and confounding by road traffic noise, which was recently associated with stroke. Here we examined the association between long-term exposure to air pollution and incidence of stroke (overall, ischemic, hemorrhagic), adjusting for road traffic noise. In a nationwide Danish Nurse Cohort consisting of 23,423 nurses, recruited in 1993 or 1999, we identified 1,078 incident cases of stroke (944 ischemic and 134 hemorrhagic) up to December 31, 2014, defined as first-ever hospital contact. The full residential address histories since 1970 were obtained for each participant and the annual means of air pollutants (particulate matter with diameter < 2.5 µm and < 10 µm (PM2.5 and PM10), nitrogen dioxide (NO2), nitrogen oxides (NOx)) and road traffic noise were determined using validated models. Time-varying Cox regression models were used to estimate hazard ratios (HR) (95% confidence intervals (CI)) for the associations of one-, three, and 23-year running mean of air pollutants with stroke adjusting for potential confounders and noise. In fully adjusted models, the HRs (95% CI) per interquartile range increase in one-year running mean of PM2.5 and overall, ischemic, and hemorrhagic stroke were 1.12 (1.01-1.25), 1.13 (1.01-1.26), and 1.07 (0.80-1.44), respectively, and remained unchanged after adjustment for noise. Long-term exposure to ambient PM2.5 was associated with the risk of stroke independent of road traffic noise.

We used the EVAv6.0 system to estimate the present (2015) and future (2015-2050) global PM_2.5 and O₃-related premature mortalities, using simulated surface concentrations from the GISS-E2.1-G Earth system model. The PM_2.5-related global premature mortality is estimated to be 4.3 and 4.4 million by the non-linear and linear models, respectively. Ischemic heart diseases are found to be the leading cause of PM_2.5-related premature deaths, contributing by 35% globally. Both long-term and short-term O₃-related premature deaths are estimated to be around 1 million, globally. Overall, PM_2.5 and O₃-related premature mortality leads to 5.3-5.4 million premature deaths, globally. The global burden of premature deaths is mainly driven by the Asian region, which in 2015 contributes by 75% of the total global premature deaths. An increase from 6.2% to 8% in the PM_2.5 relative risk as recommended by the WHO leads to an increase of PM_2.5-related premature mortality by 28%, to 5.7 million. Finally, bias correcting the simulated PM_2.5 concentrations in 2015 leads to an increase of up to 73% in the global PM_2.5-related premature mortality, leading to a total number of global premature deaths of up to 7.7 million, implying the necessity of bias correction to get more robust health burden estimates. PM_2.5 and O₃-related premature mortality in 2050 decreases by up to 57% and 18%, respectively, due to emission reductions alone. However, the projected increase and aging of the population leads to increases of premature mortality by up to a factor of 2, showing that the population exposed to air pollution is more important than the level of air pollutants, highlighting that the population dynamics should be considered when setting up health assessment systems.

A local-scale Gaussian dispersion-deposition model (OML-DEP) has been coupled to a regional chemistry-transport model (DEHM with a resolution of approximately 6 km × 6 km over Denmark) in the Danish Ammonia Modelling System, DAMOS. Thereby, it has been possible to model the distribution of ammonia concentrations and depositions on a spatial resolution down to 400 m × 400 m for selected areas in Denmark. DAMOS has been validated against measured concentrations from the dense measuring network covering Denmark. Here measured data from 21 sites are included and the validation period covers 2–5 years within the period 2005–2009. A standard time series analysis (using statistic parameters like correlation and bias) shows that the coupled model system captures the measured time series better than the regional- scale model alone. However, our study also shows that about 50% of the modelled concentration level at a given location originates from non-local emission sources. The local-scale model covers a domain of 16 km × 16 km, and of the locally released ammonia (NH₃) within this domain, our simulations at five sites show that 14–27% of the locally (within 16 km × 16 km) emitted NH₃ also deposits locally. These results underline the importance of including both high-resolution local-scale modelling of NH₃ as well as the regional-scale component described by the regional model. The DAMOS system can be used as a tool in environmental management in relation to assessments of total nitrogen load of sensitive nature areas in intense agricultural regions. However, high spatio-temporal resolution in input parameters like NH₃ emissions and land-use data is required.