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Air pollution is an important cause of adverse health effects, even in the Nordic countries, which have relatively good air quality. Modelling-based air quality assessment of the health impacts relies on reliable model estimates of ambient air pollution concentrations, which furthermore rely on good-quality spatially resolved emission data. While quantitative emission estimates are the cornerstone of good emission data, description of the spatial distribution of the emissions is especially important for local air quality modelling at high resolution. In this paper we present a new air pollution emission inventory for the Nordic countries with high-resolution spatial allocation (1 km × 1 km) covering the years 1990, 1995, 2000, 2005, 2010, 2012, and 2014. The inventory is available at https://doi.org/10.5281/zenodo.10571094 (Paunu et al., 2023). To study the impact of applying national data and methods to the spatial distribution of the emissions, we compared road transport and machinery and off-road sectors to CAMS-REGv4.2, which used a consistent spatial distribution method throughout Europe for each sector. Road transport is a sector with well-established proxies for spatial distribution, while for the machinery and off-road sector, the choice of proxies is not as straightforward as it includes a variety of different type of vehicles and machines operating in various environments. We found that CAMS-REGv4.2 was able to produce similar spatial patterns to our Nordic inventory for the selected sectors. However, the resolution of our Nordic inventory allows for more detailed impact assessment than CAMS-REGv4.2, which had a resolution of 0.1° × 0.05° (longitude–latitude, roughly 5.5 km × 3.5–6.5 km in the Nordic countries). The EMEP/EEA Guidebook chapter on spatial mapping of emissions has recommendations for the sectoral proxies. Based on our analysis we argue that the guidebook should have separate recommendations for proxies for several sub-categories of the machinery and off-road sectors, instead of including them within broader sectors. We suggest that land use data are the best starting point for proxies for many of the subsectors, and they can be combined with other suitable data to enhance the spatial distribution. For road transport, measured traffic flow data should be utilized where possible, to support modelled data in the proxies.

This review provides a community's perspective on air quality research focusing mainly on developments over the past decade. The article provides perspectives on current and future challenges as well as research needs for selected key topics. While this paper is not an exhaustive review of all research areas in the field of air quality, we have selected key topics that we feel are important from air quality research and policy perspectives. After providing a short historical overview, this review focuses on improvements in characterizing sources and emissions of air pollution, new air quality observations and instrumentation, advances in air quality prediction and forecasting, understanding interactions of air quality with meteorology and climate, exposure and health assessment, and air quality management and policy. In conducting the review, specific objectives were (i) to address current developments that push the boundaries of air quality research forward, (ii) to highlight the emerging prominent gaps of knowledge in air quality research, and (iii) to make recommendations to guide the direction for future research within the wider community. This review also identifies areas of particular importance for air quality policy. The original concept of this review was borne at the International Conference on Air Quality 2020 (held online due to the COVID 19 restrictions during 18–26 May 2020), but the article incorporates a wider landscape of research literature within the field of air quality science. On air pollution emissions the review highlights, in particular, the need to reduce uncertainties in emissions from diffuse sources, particulate matter chemical components, shipping emissions, and the importance of considering both indoor and outdoor sources. There is a growing need to have integrated air pollution and related observations from both ground-based and remote sensing instruments, including in particular those on satellites. The research should also capitalize on the growing area of low-cost sensors, while ensuring a quality of the measurements which are regulated by guidelines. Connecting various physical scales in air quality modelling is still a continual issue, with cities being affected by air pollution gradients at local scales and by long-range transport. At the same time, one should allow for the impacts from climate change on a longer timescale. Earth system modelling offers considerable potential by providing a consistent framework for treating scales and processes, especially where there are significant feedbacks, such as those related to aerosols, chemistry, and meteorology. Assessment of exposure to air pollution should consider the impacts of both indoor and outdoor emissions, as well as application of more sophisticated, dynamic modelling approaches to predict concentrations of air pollutants in both environments. With particulate matter being one of the most important pollutants for health, research is indicating the urgent need to understand, in particular, the role of particle number and chemical components in terms of health impact, which in turn requires improved emission inventories and models for predicting high-resolution distributions of these metrics over cities. The review also examines how air pollution management needs to adapt to the above-mentioned new challenges and briefly considers the implications from the COVID-19 pandemic for air quality. Finally, we provide recommendations for air quality research and support for policy.

Overall, European air quality has worsened in recent decades as a consequence of increased anthropogenic emissions, in particular from the power generation sector. The evidence of the effects of atmospheric pollution (and particularly fine particulate matter, PM2.5) on human health is now unquestionable; it is mainly associated with cardiovascular and respiratory diseases, along with morbidity and even mortality. These effects may even strengthen in the future as a consequence of climate penalties and future changes in the projected population. For all these reasons, the main objective of this contribution is the estimation of the annual excess premature deaths (PD) associated with PM2.5 in the present (1991–2010) and future (2031–2050) European population using non-linear exposure–response functions. The endpoints included are lung cancer (LC), chronic obstructive pulmonary disease (COPD), low respiratory infections (LRI), ischaemic heart disease (IHD), cerebrovascular disease (CEV) and other non-communicable diseases (other NCD). PM2.5 concentrations come from coupled chemistry–climate regional simulations under present and future (RCP8.5) scenarios. The cases assessed include the estimation of the present incidence of PD (PRE-P2010), the quantification of the role of a changing climate in PD (FUT-P2010) and the importance of changes in the population projected for the year 2050 in the incidence of excess PD (FUT-P2050). Two additional cases (REN80-P2010 and REN80-P2050) evaluate the impact on premature mortality rates of a mitigation scenario in which 80 % of European energy production comes from renewable sources. The results indicate that PM2.5 accounts for nearly 895 000 (95 % confidence interval (95 % CI) 725 000–1 056 000) annual excess PD over Europe, with IHD being the largest contributor to premature mortality associated with fine particles in both present and future scenarios. The case that isolates the effects of a climate penalty (FUT-P2010) estimates a variation of +0.2 % in mortality rates over the whole domain. However, under this scenario, the incidence of PD over central Europe will benefit from a decrease in PM2.5 (−2.2 PD/100 000 inhabitants), while in eastern (+1.3 PD/100 000 inhabitants) and western (+0.4 PD/100 000 inhabitants) Europe, PD will increase due to increased PM2.5 levels. The changes in the projected population (FUT-P2050) will lead to a large increase in annual excess PD (1 540 000, 95 % CI 1 247 000–1 818 000; +71.96 % with respect to PRE-P2010 and +71.67 % with respect to FUT-P2010) due to the ageing of the European population. Last, the mitigation scenario (REN80-P2050) demonstrates that the effects of a mitigation policy of increasing the ratio of renewable sources in the energy mix could lead to a decrease of over 60 000 (95 % CI 48 500–70 900) annual PD for the year 2050 (a decrease of −4 % in comparison with the no-mitigation scenario FUT-P2050). In spite of the uncertainties inherent in future estimations, this contribution reveals the need of governments and public entities to take action and choose air pollution mitigation policies.

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 (SECAs) 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.

This study provides a comprehensive assessment of NO2 changes across the main European urban areas induced by COVID-19 lockdowns using satellite retrievals from the Tropospheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5p satellite, surface site measurements, and simulations from the Copernicus Atmosphere Monitoring Service (CAMS) regional ensemble of air quality models. Some recent TROPOMI-based estimates of changes in atmospheric NO2 concentrations have neglected the influence of weather variability between the reference and lockdown periods. Here we provide weather-normalized estimates based on a machine learning method (gradient boosting) along with an assessment of the biases that can be expected from methods that omit the influence of weather. We also compare the weather-normalized satellite-estimated NO2 column changes with weather-normalized surface NO2 concentration changes and the CAMS regional ensemble, composed of 11 models, using recently published estimates of emission reductions induced by the lockdown. All estimates show similar NO2 reductions. Locations where the lockdown measures were stricter show stronger reductions, and, conversely, locations where softer measures were implemented show milder reductions in NO2 pollution levels. Average reduction estimates based on either satellite observations (−23 %), surface stations (−43 %), or models (−32 %) are presented, showing the importance of vertical sampling but also the horizontal representativeness. Surface station estimates are significantly changed when sampled to the TROPOMI overpasses (−37 %), pointing out the importance of the variability in time of such estimates. Observation-based machine learning estimates show a stronger temporal variability than model-based estimates.

Residential wood combustion (RWC) is an important contributor to air quality in numerous regions worldwide. This study is the first extensive evaluation of the influence of RWC on ambient air quality in several Nordic cities. We have analysed the emissions and concentrations of PM2.5 in cities within four Nordic countries: in the metropolitan areas of Copenhagen, Oslo, and Helsinki and in the city of Umeå. We have evaluated the emissions for the relevant urban source categories and modelled atmospheric dispersion on regional and urban scales. The emission inventories for RWC were based on local surveys, the amount of wood combusted, combustion technologies and other relevant factors. The accuracy of the predicted concentrations was evaluated based on urban concentration measurements. The predicted annual average concentrations ranged spatially from 4 to 7 µg m−3 (2011), from 6 to 10 µg m−3 (2013), from 4 to more than 13 µg m−3 (2013) and from 9 to more than 13 µg m−3 (2014), in Umeå, Helsinki, Oslo and Copenhagen, respectively. The higher concentrations in Copenhagen were mainly caused by the relatively high regionally and continentally transported background contributions. The annual average fractions of PM2.5 concentrations attributed to RWC within the considered urban regions ranged spatially from 0 % to 15 %, from 0 % to 20 %, from 8 % to 22 % and from 0 % to 60 % in Helsinki, Copenhagen, Umeå and Oslo, respectively. In particular, the contributions of RWC in central Oslo were larger than 40 % as annual averages. In Oslo, wood combustion was used mainly for the heating of larger blocks of flats. In contrast, in Helsinki, RWC was solely used in smaller detached houses. In Copenhagen and Helsinki, the highest fractions occurred outside the city centre in the suburban areas. In Umeå, the highest fractions occurred both in the city centre and its surroundings.

This modeling study presents the sectoral contributions of anthropogenic emissions in the four Nordic countries (Denmark, Finland, Norway and Sweden) on air pollution levels and the associated health impacts and costs over the Nordic and the Arctic regions for the year 2015. The Danish Eulerian Hemispheric Model (DEHM) has been used on a 50 km resolution over Europe in tagged mode in order to calculate the response of a 30 % reduction of each emission sector in each Nordic country individually. The emission sectors considered in the study were energy production, non-industrial/commercial heating, industry, traffic, off-road mobile sources and waste management/agriculture. In total, 28 simulations were carried out. Following the air pollution modeling, the Economic Valuation of Air Pollution (EVA) model has been used to calculate the associated premature mortality and their costs. Results showed that more than 80 % of the PM2.5 concentration was attributed to transport from outside these four countries, implying an effort outside the Nordic region in order to decrease the pollutant levels over the area. The leading emission sector in each country was found to be non-industrial combustion (contributing by more than 60 % to the total PM2.5 mass coming from the country itself), except for Sweden, where industry contributed to PM2.5 with a comparable amount to non-industrial combustion. In addition to non-industrial combustion, the next most important source categories were industry, agriculture and traffic. The main chemical constituent of PM2.5 concentrations that comes from the country itself is calculated to be organic carbon in all countries, which suggested that non-industrial wood burning was the dominant national source of pollution in the Nordic countries. We have estimated the total number of premature mortality cases due to air pollution to be around 4000 in Denmark and Sweden and around 2000 in Finland and Norway. These premature mortality cases led to a total cost of EUR 7 billion in the selected Nordic countries. The assessment of the related premature mortality and associated cost estimates suggested that non-industrial combustion, together with industry and traffic, will be the main sectors to be targeted in emission mitigation strategies in the future.

Although coastal regions only amount to 7 % of the global oceans, their contribution to the global oceanic air–sea CO2 exchange is proportionally larger, with fluxes in some estuaries being similar in magnitude to terrestrial surface fluxes of CO2. Across a heterogeneous surface consisting of a coastal marginal sea with estuarine properties and varied land mosaics, the surface fluxes of CO2 from both marine areas and terrestrial surfaces were investigated in this study together with their impact in atmospheric CO2 concentrations by the usage of a high-resolution modelling framework. The simulated terrestrial fluxes across the study region of Denmark experienced an east–west gradient corresponding to the distribution of the land cover classification, their biological activity and the urbanised areas. Annually, the Danish terrestrial surface had an uptake of approximately −7000 GgC yr−1. While the marine fluxes from the North Sea and the Danish inner waters were smaller annually, with about −1800 and 1300 GgC yr−1, their sizes are comparable to annual terrestrial fluxes from individual land cover classifications in the study region and hence are not negligible. The contribution of terrestrial surfaces fluxes was easily detectable in both simulated and measured concentrations of atmospheric CO2 at the only tall tower site in the study region. Although, the tower is positioned next to Roskilde Fjord, the local marine impact was not distinguishable in the simulated concentrations. But the regional impact from the Danish inner waters and the Baltic Sea increased the atmospheric concentration by up to 0.5 ppm during the winter months.

The evaluation and intercomparison of air quality models is key to reducing model errors and uncertainty. The projects AQMEII3 and EURODELTA-Trends, in the framework of the Task Force on Hemispheric Transport of Air Pollutants and the Task Force on Measurements and Modelling, respectively (both task forces under the UNECE Convention on the Long Range Transport of Air Pollution, LTRAP), have brought together various regional air quality models to analyze their performance in terms of air concentrations and wet deposition, as well as to address other specific objectives.This paper jointly examines the results from both project communities by intercomparing and evaluating the deposition estimates of reduced and oxidized nitrogen (N) and sulfur (S) in Europe simulated by 14 air quality model systems for the year 2010. An accurate estimate of deposition is key to an accurate simulation of atmospheric concentrations. In addition, deposition fluxes are increasingly being used to estimate ecological impacts. It is therefore important to know by how much model results differ and how well they agree with observed values, at least when comparison with observations is possible, such as in the case of wet deposition.This study reveals a large variability between the wet deposition estimates of the models, with some performing acceptably (according to previously defined criteria) and others underestimating wet deposition rates. For dry deposition, there are also considerable differences between the model estimates. An ensemble of the models with the best performance for N wet deposition was made and used to explore the implications of N deposition in the conservation of protected European habitats. Exceedances of empirical critical loads were calculated for the most common habitats at a resolution of 100  ×  100 m2 within the Natura 2000 network, and the habitats with the largest areas showing exceedances are determined.Moreover, simulations with reduced emissions in selected source areas indicated a fairly linear relationship between reductions in emissions and changes in the deposition rates of N and S. An approximate 20 % reduction in N and S deposition in Europe is found when emissions at a global scale are reduced by the same amount. European emissions are by far the main contributor to deposition in Europe, whereas the reduction in deposition due to a decrease in emissions in North America is very small and confined to the western part of the domain. Reductions in European emissions led to substantial decreases in the protected habitat areas with critical load exceedances (halving the exceeded area for certain habitats), whereas no change was found, on average, when reducing North American emissions in terms of average values per habitat.

In the framework of the third phase of the Air Quality Model Evaluation International Initiative (AQMEII3), and as contribution to the second phase of the Hemispheric Transport of Air Pollution (HTAP2) activities for Europe and North America, the impacts of a 20 % decrease of global and regional anthropogenic emissions on surface air pollutant levels in 2010 are simulated by an international community of regional-scale air quality modeling groups, using different state-of-the-art chemistry and transport models (CTMs). The emission perturbations at the global level, as well as over the HTAP2-defined regions of Europe, North America and East Asia, are first simulated by the global Composition Integrated Forecasting System (C-IFS) model from European Centre for Medium-Range Weather Forecasts (ECMWF), which provides boundary conditions to the various regional CTMs participating in AQMEII3. On top of the perturbed boundary conditions, the regional CTMs used the same set of perturbed emissions within the regional domain for the different perturbation scenarios that introduce a 20 % reduction of anthropogenic emissions globally as well as over the HTAP2-defined regions of Europe, North America and East Asia. Results show that the largest impacts over both domains are simulated in response to the global emission perturbation, mainly due to the impact of domestic emission reductions. The responses of NO2, SO2 and PM concentrations to a 20 % anthropogenic emission reduction are almost linear (∼ 20 % decrease) within the global perturbation scenario with, however, large differences in the geographical distribution of the effect. NO2, CO and SO2 levels are strongly affected over the emission hot spots. O3 levels generally decrease in all scenarios by up to ∼ 1 % over Europe, with increases over the hot spot regions, in particular in the Benelux region, by an increase up to ∼ 6 % due to the reduced effect of NOx titration. O3 daily maximum of 8 h running average decreases in all scenarios over Europe, by up to ∼ 1 %. Over the North American domain, the central-to-eastern part and the western coast of the US experience the largest response to emission perturbations. Similar but slightly smaller responses are found when domestic emissions are reduced. The impact of intercontinental transport is relatively small over both domains, however, still noticeable particularly close to the boundaries. The impact is noticeable up to a few percent, for the western parts of the North American domain in response to the emission reductions over East Asia. O3 daily maximum of 8 h running average decreases in all scenarios over north Europe by up to ∼ 5 %. Much larger reductions are calculated over North America compared to Europe. In addition, values of the Response to Extra-Regional Emission Reductions (RERER) metric have been calculated in order to quantify the differences in the strengths of non-local source contributions to different species among the different models. We found large RERER values for O3 (∼ 0.8) over both Europe and North America, indicating a large contribution from non-local sources, while for other pollutants including particles, low RERER values reflect a predominant control by local sources. A distinct seasonal variation in the local vs. non-local contributions has been found for both O3 and PM2.5, particularly reflecting the springtime long-range transport to both continents.

The impact of air pollution on human health and the associated external costs in Europe and the United States (US) for the year 2010 are modeled by a multi-model ensemble of regional models in the frame of the third phase of the Air Quality Modelling Evaluation International Initiative (AQMEII3). The modeled surface concentrations of O3, CO, SO2 and PM2.5 are used as input to the Economic Valuation of Air Pollution (EVA) system to calculate the resulting health impacts and the associated external costs from each individual model. Along with a base case simulation, additional runs were performed introducing 20 % anthropogenic emission reductions both globally and regionally in Europe, North America and east Asia, as defined by the second phase of the Task Force on Hemispheric Transport of Air Pollution (TF-HTAP2). Health impacts estimated by using concentration inputs from different chemistry–transport models (CTMs) to the EVA system can vary up to a factor of 3 in Europe (12 models) and the United States (3 models). In Europe, the multi-model mean total number of premature deaths (acute and chronic) is calculated to be 414 000, while in the US, it is estimated to be 160 000, in agreement with previous global and regional studies. The economic valuation of these health impacts is calculated to be EUR 300 billion and 145 billion in Europe and the US, respectively. A subset of models that produce the smallest error compared to the surface observations at each time step against an all-model mean ensemble results in increase of health impacts by up to 30 % in Europe, while in the US, the optimal ensemble mean led to a decrease in the calculated health impacts by ∼ 11 %. A total of 54 000 and 27 500 premature deaths can be avoided by a 20 % reduction of global anthropogenic emissions in Europe and the US, respectively. A 20 % reduction of North American anthropogenic emissions avoids a total of ∼ 1000 premature deaths in Europe and 25 000 total premature deaths in the US. A 20 % decrease of anthropogenic emissions within the European source region avoids a total of 47 000 premature deaths in Europe. Reducing the east Asian anthropogenic emissions by 20 % avoids ∼ 2000 total premature deaths in the US. These results show that the domestic anthropogenic emissions make the largest impacts on premature deaths on a continental scale, while foreign sources make a minor contribution to adverse impacts of air pollution.

The impact of climate change on sea salt aerosol production, dispersion, and fate over Europe is studied using four offline regional chemistry transport models driven by the climate scenario SRES A1B over two periods: 1990–2009 and 2040–2059. This study is focused mainly on European seas: Baltic, Black, North, and Mediterranean. The differences and similarities between the individual models' predictions of the impact on sea salt emission, concentration, and deposition due to changes in wind gusts and seawater temperature are analysed. The results show that the major driver for the sea salt flux changes will be the seawater temperature, as wind speed is projected to stay nearly the same. There are, however, substantial differences between the model predictions and their sensitivity to changing seawater temperature, which demonstrates substantial lack of current understanding of the sea salt flux predictions. Although seawater salinity changes are not evaluated in this study, sensitivity of sea salt aerosol production to salinity is similarly analysed, showing once more the differences between the different models. An assessment of the impact of sea salt aerosol on the radiative balance is presented.

The goal of the Tropospheric Ozone Assessment Report (TOAR) is to provide the research community with an up-to-date scientific assessment of tropospheric ozone, from the surface to the tropopause. While a suite of observations provides significant information on the spatial and temporal distribution of tropospheric ozone, observational gaps make it necessary to use global atmospheric chemistry models to synthesize our understanding of the processes and variables that control tropospheric ozone abundance and its variability. Models facilitate the interpretation of the observations and allow us to make projections of future tropospheric ozone and trace gas distributions for different anthropogenic or natural perturbations. This paper assesses the skill of current-generation global atmospheric chemistry models in simulating the observed present-day tropospheric ozone distribution, variability, and trends. Drawing upon the results of recent international multi-model intercomparisons and using a range of model evaluation techniques, we demonstrate that global chemistry models are broadly skillful in capturing the spatio-temporal variations of tropospheric ozone over the seasonal cycle, for extreme pollution episodes, and changes over interannual to decadal periods. However, models are consistently biased high in the northern hemisphere and biased low in the southern hemisphere, throughout the depth of the troposphere, and are unable to replicate particular metrics that define the longer term trends in tropospheric ozone as derived from some background sites. When the models compare unfavorably against observations, we discuss the potential causes of model biases and propose directions for future developments, including improved evaluations that may be able to better diagnose the root cause of the model-observation disparity. Overall, model results should be approached critically, including determining whether the model performance is acceptable for the problem being addressed, whether biases can be tolerated or corrected, whether the model is appropriately constituted, and whether there is a way to satisfactorily quantify the uncertainty.

The Danish Eulerian Hemispheric Model (DEHM) was applied to investigate how projected climate changes will affect the atmospheric transport of 13 persistent organic pollutants (POPs) to the Arctic and their environmental fate within the Arctic. Three sets of simulations were performed, one with present day emissions and initial environmental concentrations from a 20-year spin-up simulation, one with present day emissions and with initial environmental concentrations set to zero and one without emissions but with initial environmental concentrations from the 20-year spin-up simulation. Each set of simulations consisted of two 10-year time slices representing the present (1990–2000) and future (2090–2100) climate conditions. DEHM was driven using meteorological input from the global circulation model, ECHAM/MPI-OM, simulating the SRES (Special Report on Emissions Scenarios) A1B climate scenario. Under the applied climate and emission scenarios, the total mass of all compounds was predicted to be up to 55 % lower across the Northern Hemisphere at the end of the 2090s than in the 1990s. The mass of HCHs within the Arctic was predicted to be up to 38 % higher, whereas the change in mass of the PCBs was predicted to range from 38 % lower to 17 % higher depending on the congener and the applied initial environmental concentrations. The results of this study also indicate that contaminants with no or a short emission history will be more rapidly transported to and build up in the arctic environment in a future warmer climate. The process that dominates the environmental behaviour of POPs in the Arctic under a future warmer climate scenario is the shift in mass of POPs from the surface media to the atmosphere induced by the higher mean temperature. This is to some degree counteracted by higher degradation rates also following the higher mean temperature. The more dominant of these two processes depends on the physical-chemical properties of the compounds. Previous model studies have predicted that the effect of a changed climate on the transport of POPs to the Arctic is moderate relative to the effect of proposed changes in emissions, which is confirmed in this study. However, the model studies do not agree on whether climate change acts to reduce or increase environmental concentrations of POPs in the Arctic, and further work is needed to resolve this matter.

Minimising the uncertainties in estimates of air–sea CO2 exchange is an important step toward increasing the confidence in assessments of the CO2 cycle. Using an atmospheric transport model makes it possible to investigate the direct impact of atmospheric parameters on the air–sea CO2 flux along with its sensitivity to, for example, short-term temporal variability in wind speed, atmospheric mixing height and atmospheric CO2 concentration. With this study, the importance of high spatiotemporal resolution of atmospheric parameters for the air–sea CO2 flux is assessed for six sub-basins within the Baltic Sea and Danish inner waters. A new climatology of surface water partial pressure of CO2 (pCO2w) has been developed for this coastal area based on available data from monitoring stations and on-board pCO2w measuring systems. Parameterisations depending on wind speed were applied for the transfer velocity to calculate the air–sea CO2 flux. Two model simulations were conducted – one including short-term variability in atmospheric CO2 (VAT), and one where it was not included (CAT). A seasonal cycle in the air–sea CO2 flux was found for both simulations for all sub-basins with uptake of CO2 in summer and release of CO2 to the atmosphere in winter. During the simulated period 2005–2010, the average annual net uptake of atmospheric CO2 for the Baltic Sea, Danish straits and Kattegat was 287 and 471 Gg C yr−1 for the VAT and CAT simulations, respectively. The obtained difference of 184 Gg C yr−1 was found to be significant, and thus ignoring short-term variability in atmospheric CO2 does have a sizeable effect on the air–sea CO2 exchange. The combination of the atmospheric model and the new pCO2w fields has also made it possible to make an estimate of the marine part of the Danish CO2 budget for the first time. A net annual uptake of 2613 Gg C yr−1 was found for the Danish waters. A large uncertainty is connected to the air–sea CO2 flux in particular caused by the transfer velocity parameterisation and the applied pCO2w climatology. However, as a significant difference of 184 Gg C yr−1 is obtained between the VAT and CAT simulations, the present study underlines the importance of including short-term variability in atmospheric CO2 concentration in future model studies of the air–sea exchange in order to minimise the uncertainty.

The impact of climate and emissions changes on the deposition of reactive nitrogen (Nr) over Europe was studied using four offline regional chemistry transport models (CTMs) driven by the same global projection of future climate over the period 2000–2050. Anthropogenic emissions for the years 2005 and 2050 were used for simulations of both present and future periods in order to isolate the impact of climate change, hemispheric boundary conditions and emissions, and to assess the robustness of the results across the different models. The results from these four CTMs clearly show that the main driver of future N-deposition changes is the specified emission change. Under the specified emission scenario for 2050, emissions of oxidised nitrogen were reduced substantially, whereas emissions of NH3 increase to some extent, and these changes are largely reflected in the modelled concentrations and depositions. The lack of sulfur and oxidised nitrogen in the future atmosphere results in a much larger fraction of NHx being present in the form of gaseous ammonia. Predictions for wet and total deposition were broadly consistent, although the three fine-scale models resolve European emission areas and changes better than the hemispheric-scale model. The biggest difference in the models is for predictions of individual N compounds. One model (EMEP) was used to explore changes in critical loads, also in conjunction with speculative climate-induced increases in NH3 emissions. These calculations suggest that the area of ecosystems that exceeds critical loads is reduced from 64% for year 2005 emissions levels to 50% for currently estimated 2050 levels. A possible climate-induced increase in NH3 emissions could worsen the situation, with areas exceeded increasing again to 57% (for a 30% NH3 emission increase).

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.

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.

The understanding of biochemical feedback mechanisms in the climate system is lacking knowledge in relation to bi-directional ammonia (NH3) exchange between natural ecosystems and the atmosphere. We therefore study the atmospheric NH3 fluxes during a 25-day period during autumn 2010 (21 October to 15 November) for the Danish beech forest Lille Bøgeskov to address the hypothesis that NH3 emissions occur from deciduous forests in relation to leaf fall. This is accomplished by using observations of vegetation status, NH3 fluxes and model calculations. Vegetation status was observed using plant area index (PAI) and leaf area index (LAI). NH3 fluxes were measured using the relaxed eddy accumulation (REA) method. The REA-based NH3 concentrations were compared to NH3 denuder measurements. Model calculations of the atmospheric NH3 concentration were obtained with the Danish Ammonia MOdelling System (DAMOS). The relative contribution from the forest components to the atmospheric NH3 flux was assessed using a simple two-layer bi-directional canopy compensation point model. A total of 57.7% of the fluxes measured showed emission and 19.5% showed deposition. A clear tendency of the flux going from deposition of −0.25 ± 0.30 μg NH3-N m−2 s−1 to emission of up to 0.67 ± 0.28 μg NH3-N m−2 s−1 throughout the measurement period was found. In the leaf fall period (23 October to 8 November), an increase in the atmospheric NH3 concentrations was related to the increasing forest NH3 flux. Following leaf fall, the magnitude and temporal structure of the measured NH3 emission fluxes could be adequately reproduced with the bi-directional resistance model; it suggested the forest ground layer (soil and litter) to be the main contributing component to the NH3 emissions. The modelled concentration from DAMOS fits well the measured concentrations before leaf fall, but during and after leaf fall, the modelled concentrations are too low. The results indicate that the missing contribution to atmospheric NH3 concentration from vegetative surfaces related to leaf fall are of a relatively large magnitude. We therefore conclude that emissions from deciduous forests are important to include in model calculations of atmospheric NH3 for forest ecosystems. Finally, diurnal variations in the measured NH3 concentrations were related to meteorological conditions, forest phenology and the spatial distribution of local anthropogenic NH3 sources. This suggests that an accurate description of ammonia fluxes over forest ecosystems requires a dynamic description of atmospheric and vegetation processes.

We present here a dynamical method for modelling temporal and geographical variations in ammonia emissions in regional-scale chemistry transport models (CTMs) and chemistry climate models (CCMs). The method is based on the meteorology in the models and gridded inventories. We use the dynamical method to investigate the spatiotemporal variability of ammonia emissions across part of Europe and study how these emissions are related to geographical and year-to-year variations in atmospheric temperature alone. For simplicity we focus on the emission from a storage facility related to a standard Danish pig stable with 1000 animals and display how emissions from this source would vary geographically throughout central and northern Europe and from year to year. In view of future climate changes, we also evaluate the potential future changes in emission by including temperature projections from an ensemble of climate models. The results point towards four overall issues. (1) Emissions can easily vary by 20% for different geographical locations within a country due to overall variations in climate. The largest uncertainties are seen for large countries such as the UK, Germany and France. (2) Annual variations in overall climate can at specific locations cause uncertainties in the range of 20%. (3) Climate change may increase emissions by 0–40% in central to northern Europe. (4) Gradients in existing emission inventories that are seen between neighbour countries (e.g. between the UK and France) can be reduced by using a dynamical methodology for calculating emissions. Acting together these four factors can cause substantial uncertainties in emission. Emissions are generally considered among the largest uncertainties in the model calculations made with CTM and CCM models. Efforts to reduce uncertainties are therefore highly relevant. It is therefore recommended that both CCMs and CTMs implement a dynamical methodology for simulating ammonia emissions in a similar way as for biogenic volatile organic compound (BVOCs) – a method that has been used for more than a decade in CTMs. Finally, the climate penalty on ammonia emissions should be taken into account at the policy level such as the NEC and IPPC directives.

We examine here the hypothesis that during flowering, the grass pollen concentrations at a specific site reflect the distribution of grass pollen sources within a few kilometres of this site. We perform this analysis on data from a measurement campaign in the city of Aarhus (Denmark) using three pollen traps and by comparing these observations with a novel inventory of grass pollen sources. The source inventory is based on a new methodology developed for urban-scale grass pollen sources. The new methodology is believed to be generally applicable for the European area, as it relies on commonly available remote sensing data combined with management information for local grass areas. The inventory has identified a number of grass pollen source areas present within the city domain. The comparison of the measured pollen concentrations with the inventory shows that the atmospheric concentrations of grass pollen in the urban zone reflect the source areas identified in the inventory, and that the pollen sources that are found to affect the pollen levels are located near or within the city domain. The results also show that during days with peak levels of pollen concentrations there is no correlation between the three urban traps and an operational trap located just 60 km away. This finding suggests that during intense flowering, the grass pollen concentration mirrors the local source distribution and is thus a local-scale phenomenon. Model simulations aimed at assessing population exposure to pollen levels are therefore recommended to take into account both local sources and local atmospheric transport, and not to rely only on describing regional to long-range transport of pollen. The derived pollen source inventory can be entered into local-scale atmospheric transport models in combination with other components that simulate pollen release in order to calculate urban-scale variations in the grass pollen load. The gridded inventory with a resolution of 14 m is therefore made available as supplementary material to this paper, and the verifying grass pollen observations are additionally available in tabular form.

The impact of climate change on surface ozone over Europe was studied using four offline regional chemistry transport models (CTMs) and one online regional integrated climate-chemistry model (CCM), driven by the same global projection of future climate under the SRES A1B scenario. Anthropogenic emissions of ozone precursors from RCP4.5 for year 2000 were used for simulations of both present and future periods in order to isolate the impact of climate change and to assess the robustness of the results across the different models. The sensitivity of the simulated surface ozone to changes in climate between the periods 2000–2009 and 2040–2049 differs by a factor of two between the models, but the general pattern of change with an increase in southern Europe is similar across different models. Emissions of isoprene differ substantially between different CTMs ranging from 1.6 to 8.0 Tg yr−1 for the current climate, partly due to differences in horizontal resolution of meteorological input data. Also the simulated change in total isoprene emissions varies substantially across models explaining part of the different climate response on surface ozone. Ensemble mean changes in summer mean ozone and mean of daily maximum ozone are close to 1 ppb(v) in parts of the land area in southern Europe. Corresponding changes of 95-percentiles of hourly ozone are close to 2 ppb(v) in the same region. In northern Europe ensemble mean for mean and daily maximum show negative changes while there are no negative changes for the higher percentiles indicating that climate impacts on O3 could be especially important in connection with extreme summer events.

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.

The ecological status of the Baltic Sea has for many years been affected by the high input of both waterborne and airborne nutrients. The focus here is on the airborne input of nitrogen (N) and the projected changes in this input, assuming the new National Emission Ceilings directive (NEC-II), currently under negotiation in the EU, is fulfilled towards the year 2020. With a set of scenario simulations, the Danish Eulerian Hemispheric Model (DEHM) has been used to estimate the development in nitrogen deposition based on present day meteorology combined with present day (2007) or future (2020) anthropogenic emissions. Applying a so-called tagging method in the DEHM model, the contribution from ship traffic and from each of the nine countries with coastlines to the Baltic Sea has been assessed. The annual deposition to the Baltic Sea is estimated to 203 k tonnes N for the present day scenario (2007) and 165 k tonnes N in the 2020 scenario, giving a projected reduction of 38 k tonnes N in the annual load in 2020. This equals a decline in nitrogen deposition of 19%. The results from 20 model runs using the tagging method show that of the total nitrogen deposition in 2007, 52% came from emissions within the bordering countries. By 2020, this is projected to decrease to 48%. For some countries the projected decrease in nitrogen deposition arising from the implementation of the NEC-II directive will contribute significantly to compliance with the reductions agreed on in the provisional reduction targets of the Baltic Sea Action Plan. This underlines the importance of including projections like the current in future updates of the Baltic Sea Action Plan.

Inverse modeling techniques used to quantify surface carbon fluxes commonly assume that the uncertainty of fossil fuel CO2 (FFCO2) emissions is negligible and that intra-annual variations can be neglected. To investigate these assumptions, we analyzed the differences between four fossil fuel emission inventories with spatial and temporal differences over Europe and their impact on the model simulated CO2 concentration. Large temporal flux variations characterize the hourly fields (~40 % and ~80 % for the seasonal and diurnal cycles, peak-to-peak) and annual country totals differ by 10 % on average and up to 40 % for some countries (i.e., the Netherlands). These emissions have been prescribed to seven different transport models, resulting in 28 different FFCO2 concentrations fields. The modeled FFCO2 concentration time series at surface sites using time-varying emissions show larger seasonal cycles (+2 ppm at the Hungarian tall tower (HUN)) and smaller diurnal cycles in summer (−1 ppm at HUN) than when using constant emissions. The concentration range spanned by all simulations varies between stations, and is generally larger in winter (up to ~10 ppm peak-to-peak at HUN) than in summer (~5 ppm). The contribution of transport model differences to the simulated concentration std-dev is 2–3 times larger than the contribution of emission differences only, at typical European sites used in global inversions. These contributions to the hourly (monthly) std-dev's amount to ~1.2 (0.8) ppm and ~0.4 (0.3) ppm for transport and emissions, respectively. First comparisons of the modeled concentrations with 14C-based fossil fuel CO2 observations show that the large transport differences still hamper a quantitative evaluation/validation of the emission inventories. Changes in the estimated monthly biosphere flux (Fbio) over Europe, using two inverse modeling approaches, are relatively small (less that 5 %) while changes in annual Fbio (up to ~0.15 % GtC yr−1) are only slightly smaller than the differences in annual emission totals and around 30 % of the mean European ecosystem carbon sink. These results point to an urgent need to improve not only the transport models but also the assumed spatial and temporal distribution of fossil fuel emission inventories.

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.

The response of a selected number of chemical species is inspected with respect to climate change. The coupled Atmosphere-Ocean General Circulation Model ECHAM4-OPYC3 is providing meteorological fields for the Chemical long-range Transport Model DEHM. Three selected decades (1990s, 2040s and 2090s) are inspected. The 1990s are used as a reference and validation period. In this decade an evaluation of the output from the DEHM model with ECHAM4-OPYC3 meteorology input data is carried out. The model results are tested against similar model simulations with MM5 meteorology and against observations from the EMEP monitoring sites in Europe. The test results from the validation period show that the overall statistics (e.g. mean values and standard deviations) are similar for the two simulations. However, as one would expect the model setup with climate input data fails to predict correctly the timing of the variability in the observations. The overall performance of the ECHAM4-OPYC3 setup as meteorological input to the DEHM model is shown to be acceptable according to the applied ranking method. It is concluded that running a chemical long-range transport model on data from a "free run" climate model is scientifically sound. From the model runs of the three decades, it is found that the overall trend detected in the evolution of the chemical species, is the same between the 1990 decade and the 2040 decade and between the 2040 decade and the 2090 decade, respectively. The dominating impacts from climate change on a large number of the chemical species are related to the predicted temperature increase. Throughout the 21th century the ECHAM4-OPYC3 projects a global mean temperature increase of 3 K with local maxima up to 11 K in the Arctic winter based on the IPCC A2 emission scenario. As a consequence of this temperature increase, the temperature dependent biogenic emission of isoprene is predicted to increase significantly over land by the DEHM model. This leads to an increase in the O3 production and together with an increase in water vapor to an increase in the number of free OH radicals. Furthermore this increase in the number of OH radicals contributes to a significant change in the typical life time of many species, since OH are participating in a large number of chemical reactions. It is e.g. found that more SO42− will be present in the future over the already polluted areas and this increase can be explained by an enhanced conversion of SO2 to SO42−.

The CO2 source and sink distribution across Europe can be estimated in principle through inverse methods by combining CO2 observations and atmospheric transport models. Uncertainties of such estimates are mainly due to insufficient spatiotemporal coverage of CO2 observations and biases of the models. In order to assess the biases related to the use of different models the CO2 concentration field over Europe has been simulated with five different Eulerian atmospheric transport models as part of the EU-funded AEROCARB project, which has the main goal to estimate the carbon balance of Europe. In contrast to previous comparisons, here both global coarse-resolution and regional higher-resolution models are included. Continuous CO2 observations from continental, coastal and mountain sites as well as flasks sampled on aircrafts are used to evaluate the models' ability to capture the spatiotemporal variability and distribution of lower troposphere CO2 across Europe. 14CO2 is used in addition to evaluate separately fossil fuel signal predictions. The simulated concentrations show a large range of variation, with up to ~10 ppm higher surface concentrations over Western and Central Europe in the regional models with highest (mesoscale) spatial resolution. The simulation – data comparison reveals that generally high-resolution models are more successful than coarse models in capturing the amplitude and phasing of the observed short-term variability. At high-altitude stations the magnitude of the differences between observations and models and in between models is less pronounced, but the timing of the diurnal cycle is not well captured by the models. The data comparisons show also that the timing of the observed variability on hourly to daily time scales at low-altitude stations is generally well captured by all models. However, the amplitude of the variability tends to be underestimated. While daytime values are quite well predicted, nighttime values are generally underpredicted. This is a reflection of the different mixing regimes during day and night combined with different vertical resolution between models. In line with this finding, the agreement among models is increased when sampling in the afternoon hours only and when sampling the mixed portion of the PBL, which amounts to sampling at a few hundred meters above ground. The main recommendations resulting from the study for constraining land carbon sources and sinks using high-resolution concentration data and state-of-the art transport models through inverse methods are given in the following: 1) Low altitude stations are presently preferable in inverse studies. If high altitude stations are used then the model level that represents the specific sites should be applied, 2) at low altitude sites only the afternoon values of concentrations can be represented sufficiently well by current models and therefore afternoon values are more appropriate for constraining large-scale sources and sinks in combination with transport models, 3) even when using only afternoon values it is clear that data sampled several hundred meters above ground can be represented substantially more robustly in models than surface station records, which emphasize the use of tower data in inverse studies and finally 4) traditional large scale transport models seem not sufficient to resolve fine-scale features associated with fossil fuel emissions, as well as larger-scale features like the concentration distribution above the south-western Europe. It is therefore recommended to use higher resolution models for interpretation of continental data in future studies.

The Danish Eulerian Hemispheric Model (DEHM) is a 3-D dynamical atmospheric transport model originally developed to describe the atmospheric transport of sulphur into the Arctic. A new version of the model, DEHM-POP, developed to study the atmospheric transport and environmental fate of persistent organic pollutants (POPs) is presented. During environmental cycling, POPs can be deposited and re-emitted several times before reaching a final destination. A description of the exchange processes between the land/ocean surfaces and the atmosphere is included in the model to account for this multi-hop transport. The α-isomer of the pesticide hexachlorocyclohexane (α-HCH) is used as tracer in the model development. The structure of the model and processes included are described in detail. The results from a model simulation showing the atmospheric transport for the years 1991 to 1998 are presented and evaluated against measurements. The annual averaged atmospheric concentration of α-HCH for the 1990s is well described by the model; however, the shorter-term average concentration for most of the stations is not well captured. This indicates that the present simple surface description needs to be refined to get a better description of the air-surface exchange processes of POPs.

Background: Prolonged exposure to air pollution has been linked to adverse respiratory health, yet the evidence concerning its association with chronic obstructive pulmonary disease (COPD) is inconsistent. The evidence of a greenness effect on chronic respiratory diseases is limited., Objective: This study aimed to investigate the association between long-term exposure to particulate matter (PM 2.5 and PM 10 ), black carbon (BC), nitrogen dioxide (NO 2 ), ozone (O 3 ) and greenness (as measured by the normalized difference vegetation index - NDVI) and incidence of self-reported chronic bronchitis or COPD (CB/COPD)., Methods: We analyzed data from 5355 adults from 7 centers participating in the Respiratory Health in Northern Europe (RHINE) study. Mean exposures to air pollution and greenness were assessed at available residential addresses in 1990, 2000 and 2010 using air dispersion models and satellite data, respectively. Poisson regression with log person-time as an offset was employed to analyze the association between air pollution, greenness, and CB/COPD incidence, adjusting for confounders., Results: Overall, there were 328 incident cases of CB/COPD during 2010-2023. Despite wide statistical uncertainty, we found a trend for a positive association between NO 2 exposure and CB/COPD incidence, with incidence rate ratios (IRRs) per 10 μg/m³ difference ranging between 1.13 (95% CI: 0.90-1.41) in 1990 and 1.18 (95% CI: 0.96-1.45) in 2000. O 3 showed a tendency for inverse association with CB/COPD incidence (IRR from 0.84 (95% CI: 0.66-1.07) in 2000 to 0.88 (95% CI: 0.69-1.14) in 2010. No consistent association was found between PM, BC and greenness with CB/COPD incidence across different exposure time windows., Conclusion: Consistent with prior research, our study suggests that individuals exposed to higher concentrations of NO 2 may face an elevated risk of developing COPD, although evidence remains inconclusive. Greenness was not associated with CB/COPD incidence, while O 3 showed a tendency for an inverse association with the outcome., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Agriculture's global environmental impacts are widely expected to continue expanding, driven by population and economic growth and dietary changes. This Review highlights climate change as an additional amplifier of agriculture's environmental impacts, by reducing agricultural productivity, reducing the efficacy of agrochemicals, increasing soil erosion, accelerating the growth and expanding the range of crop diseases and pests, and increasing land clearing. We identify multiple pathways through which climate change intensifies agricultural greenhouse gas emissions, creating a potentially powerful climate change-reinforcing feedback loop. The challenges raised by climate change underscore the urgent need to transition to sustainable, climate-resilient agricultural systems. This requires investments that both accelerate adoption of proven solutions that provide multiple benefits, and that discover and scale new beneficial processes and food products.