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The impacts of future methane (CH4) and other precursor emission changes are investigated for surface ozone (O3) in the United Nations Economic Commission for Europe (UNECE) region excluding North America and Israel (the EMEP region, for European Monitoring and Evaluation Programme) for the year 2050. The analysis includes a current legislation (CLE) and maximum feasible technical reduction (MFR) scenario, as well as a scenario that combines MFRs with an additional dietary shift that also meets the Paris Agreement objectives with respect to greenhouse gas emissions (LOW). For each scenario, background CH4 concentrations are calculated using a probabilistic Earth system model emulator and combined with other precursor emissions in a three-dimensional Eulerian chemistry-transport model. While focus is placed on peak season maximum daily 8 h average (MDA8) O3 concentrations, a range of other indicators for health and vegetation impacts are also discussed. Our analysis shows that roughly one-third of the total peak season MDA8 reduction achieved between the 2050 CLE and MFR scenarios is attributable to CH4 reductions, resulting predominantly from CH4 emission reductions outside of the EMEP region. The impact of other precursor emission reductions is split nearly evenly between the reductions inside and outside of the EMEP region. However, the relative importance of CH4 and other precursor emission reductions is shown to depend on the choice of O3 indicator, though indicators sensitive to peak O3 show generally consistent results. The analysis also highlights the synergistic impacts of CH4 mitigation as reducing solely CH4 achieves, beyond air quality improvement, nearly two-thirds of the total global warming reduction calculated for the LOW scenario compared to the CLE case.

The Eurodelta-Trends (EDT) multi-model experiment, aimed at assessing the efficiency of emission mitigation measures in improving air quality in Europe during 1990–2010, was designed to answer a series of questions regarding European pollution trends; i.e. were there significant trends detected by observations? Do the models manage to reproduce observed trends? How close is the agreement between the models and how large are the deviations from observations? In this paper, we address these issues with respect to particulate matter (PM) pollution. An in-depth trend analysis has been performed for PM10 and PM2.5 for the period of 2000–2010, based on results from six chemical transport models and observational data from the EMEP (Cooperative Programme for Monitoring and Evaluation of the Long-range Transmission of Air Pollutants in Europe) monitoring network. Given harmonization of set-up and main input data, the differences in model results should mainly result from differences in the process formulations within the models themselves, and the spread in the model-simulated trends could be regarded as an indicator for modelling uncertainty. The model ensemble simulations indicate overall decreasing trends in PM10 and PM2.5 from 2000 to 2010, with the total reductions of annual mean concentrations by between 2 and 5 (7 for PM10) µg m−3 (or between 10 % and 30 %) across most of Europe (by 0.5–2 µg m−3 in Fennoscandia, the north-west of Russia and eastern Europe) during the studied period. Compared to PM2.5, relative PM10 trends are weaker due to large inter-annual variability of natural coarse PM within the former. The changes in the concentrations of PM individual components are in general consistent with emission reductions. There is reasonable agreement in PM trends estimated by the individual models, with the inter-model variability below 30 %–40 % over most of Europe, increasing to 50 %–60 % in the northern and eastern parts of the EDT domain. Averaged over measurement sites (26 for PM10 and 13 for PM2.5), the mean ensemble-simulated trends are −0.24 and −0.22 µg m−3 yr−1 for PM10 and PM2.5, which are somewhat weaker than the observed trends of −0.35 and −0.40 µg m−3 yr−1 respectively, partly due to model underestimation of PM concentrations. The correspondence is better in relative PM10 and PM2.5 trends, which are −1.7 % yr−1 and −2.0 % yr−1 from the model ensemble and −2.1 % yr−1 and −2.9 % yr−1 from the observations respectively. The observations identify significant trends (at the 95 % confidence level) for PM10 at 56 % of the sites and for PM2.5 at 36 % of the sites, which is somewhat less that the fractions of significant modelled trends. Further, we find somewhat smaller spatial variability of modelled PM trends with respect to the observed ones across Europe and also within individual countries. The strongest decreasing PM trends and the largest number of sites with significant trends are found for the summer season, according to both the model ensemble and observations. The winter PM trends are very weak and mostly insignificant. Important reasons for that are the very modest reductions and even increases in the emissions of primary PM from residential heating in winter. It should be kept in mind that all findings regarding modelled versus observed PM trends are limited to the regions where the sites are located. The analysis reveals considerable variability of the role of the individual aerosols in PM10 trends across European countries. The multi-model simulations, supported by available observations, point to decreases in SO4-2 concentrations playing an overall dominant role. Also, we see relatively large contributions of the trends of NH4+ and NO3- to PM10 decreasing trends in Germany, Denmark, Poland and the Po Valley, while the reductions of primary PM emissions appear to be a dominant factor in bringing down PM10 in France, Norway, Portugal, Greece and parts of the UK and Russia. Further discussions are given with respect to emission uncertainties (including the implications of not accounting for forest fires and natural mineral dust by some of the models) and the effect of inter-annual meteorological variability on the trend analysis.

The air quality downscaling model uEMEP and its combination with the EMEP MSC-W chemical transport model are used here to achieve high-resolution air quality modelling at street level in Europe. By using publicly available proxy data, this uEMEP–EMEP modelling system is applied to calculate annual mean NO2, PM2.5, PM10, and O3 concentrations for all of Europe down to 100 m resolution and is validated against all available AIRBASE monitoring stations in Europe at 25 m resolution. Downscaling is carried out on annual mean concentrations, requiring special attention to non-linear processes, such as NO2 chemistry for which frequency distributions are applied to better represent the non-linear NO2 chemistry. The downscaling shows significant improvement in NO2 concentrations for which the spatial correlation has been doubled for most countries and bias reduced from −46 % to −18 % for all stations in Europe. The downscaling of PM2.5 and PM10 does not show improvement in spatial correlation but does reduce the overall bias in the European calculations from −21 % to −11 % and from −39 % to −30 % for PM2.5 and PM10, respectively. There is improved spatial correlation in most countries after downscaling of O3 and a reduced positive bias of O3 concentrations from +16 % to +11 %. Sensitivity tests in Norway show that improvements in the emission and emission proxy data used for the downscaling can significantly improve both the NO2 and PM results. The downscaling development opens the way for improved exposure estimates, improved assessment of emissions, and detailed calculations of source contributions to exceedances in a consistent way for all of Europe at high resolution.

Secondary inorganic PM2.5 particles are formed from SOx (SO2+SO42-), NOx (NO+NO2), and NH3 emissions, through the formation of either ammonium sulfate ((NH4)2SO4) or ammonium nitrate (NH4NO3). EU limits and WHO guidelines for PM2.5 levels are frequently exceeded in Europe, in particular in the winter months. In addition the critical loads for eutrophication are exceeded in most of the European continent. Further reductions in NH3 emissions and other PM precursors beyond the 2030 requirements could alleviate some of the health burden from fine particles and also reduce the deposition of nitrogen to vulnerable ecosystems. Using the regional-scale EMEP/MSC-W model, we have studied the effects of year 2030 NH3 emissions on PM2.5 concentrations and depositions of nitrogen in Europe in light of present (2017), past (2005), and future (2030) conditions. Our calculations show that in Europe the formation of PM2.5 from NH3 to a large extent is limited by the ratio between the emissions of NH3 on one hand and SOx plus NOx on the other hand. As the ratio of NH3 to SOx and NOx is increasing, the potential to further curb PM2.5 levels through reductions in NH3 emissions is decreasing. Here we show that per gram of NH3 emissions mitigated, the resulting reductions in PM2.5 levels simulated using 2030 emissions are about a factor of 2.6 lower than when 2005 emissions are used. However, this ratio is lower in winter. Thus further reductions in the NH3 emissions in winter may have similar potential to SOx and NOx in curbing PM2.5 levels in this season. Following the expected reductions of NH3 emission, depositions of reduced nitrogen (NH3+NH4+) should also decrease in Europe. However, as the reductions in NOx emission are larger than for NH3, the fraction of total nitrogen (reduced plus oxidised nitrogen) deposited as reduced nitrogen is increasing and may exceed 60 % in most of Europe by 2030. Thus the potential for future reductions in the exceedances of critical loads for eutrophication in Europe will mainly rely on the ability to reduce NH3 emissions.

A description of the new air quality downscaling model – the urban EMEP (uEMEP) and its combination with the EMEP MSC-W model (European Monitoring and Evaluation Programme Meteorological Synthesising Centre West) – is presented. uEMEP is based on well-known Gaussian modelling principles. The uniqueness of the system is in its combination with the EMEP MSC-W model and the “local fraction” calculation contained within it. This allows the uEMEP model to be imbedded in the EMEP MSC-W model and downscaling can be carried out anywhere within the EMEP model domain, without any double counting of emissions, if appropriate proxy data are available that describe the spatial distribution of the emissions. This makes the model suitable for high-resolution calculations, down to 50 m, over entire countries. An example application, the Norwegian air quality forecasting and assessment system, is described where the entire country is modelled at a resolution of between 250 and 50 m. The model is validated against all available monitoring data, including traffic sites, in Norway. The results of the validation show good results for NO2, which has the best known emissions, and moderately good for PM10 and PM2.5. In Norway, the largest contributor to PM, even in cities, is long-range transport followed by road dust and domestic heating emissions. These contributors to PM are more difficult to quantify than NOx exhaust emission from traffic, which is the major contributor to NO2 concentrations. In addition to the validation results, a number of verification and sensitivity results are summarised. One verification showed that single annual mean calculations with a rotationally symmetric dispersion kernel give very similar results to the average of an entire year of hourly calculations, reducing the runtime for annual means by 4 orders of magnitude. The uEMEP model, in combination with EMEP MSC-W model, provides a new tool for assessing local-scale concentrations and exposure over large regions in a consistent and homogenous way and is suitable for large-scale policy applications.

Ship emissions constitute a large, and so far poorly regulated, source of air pollution. Emissions are mainly clustered along major ship routes both in open seas and close to densely populated shorelines. Major air pollutants emitted include sulfur dioxide, NOx, and primary particles. Sulfur and NOx are both major contributors to the formation of secondary fine particles (PM2.5) and to acidification and eutrophication. In addition, NOx is a major precursor for ground-level ozone. In this paper, we quantify the contributions from international shipping to European air pollution levels and depositions. This study is based on global and regional model calculations. The model runs are made with meteorology and emission data representative of the year 2017 after the tightening of the SECA (sulfur emission control area) regulations in 2015 but before the global sulfur cap that came into force in 2020. The ship emissions have been derived using ship positioning data. We have also made model runs reducing sulfur emissions by 80 % corresponding to the 2020 requirements. This study is based on model sensitivity studies perturbing emissions from different sea areas: the northern European SECA in the North Sea and the Baltic Sea, the Mediterranean Sea and the Black Sea, the Atlantic Ocean close to Europe, shipping in the rest of the world, and finally all global ship emissions together. Sensitivity studies have also been made setting lower bounds on the effects of ship plumes on ozone formation. Both global- and regional-scale calculations show that for PM2.5 and depositions of oxidised nitrogen and sulfur, the effects of ship emissions are much larger when emissions occur close to the shore than at open seas. In many coastal countries, calculations show that shipping is responsible for 10 % or more of the controllable PM2.5 concentrations and depositions of oxidised nitrogen and sulfur. With few exceptions, the results from the global and regional calculations are similar. Our calculations show that substantial reductions in the contributions from ship emissions to PM2.5 concentrations and to depositions of sulfur can be expected in European coastal regions as a result of the implementation of a 0.5 % worldwide limit of the sulfur content in marine fuels from 2020. For countries bordering the North Sea and Baltic Sea SECA, low sulfur emissions have already resulted in marked reductions in PM2.5 from shipping before 2020. For ozone, the lifetime in the atmosphere is much longer than for PM2.5, and the potential for ozone formation is much larger in otherwise pristine environments. We calculate considerable contributions from open sea shipping. As a result, we find that the largest contributions to ozone in several regions and countries in Europe are from sea areas well outside European waters.

A large fraction of the urban population in Europe is exposed to particulate matter levels above the WHO guideline value. To make more effective mitigation strategies, it is important to understand the influence on particulate matter (PM) from pollutants emitted in different European nations. In this study, we evaluate a country source contribution forecasting system aimed at assessing the domestic and transboundary contributions to PM in major European cities for an episode in December 2016. The system is composed of two models (EMEP/MSC-W rv4.15 and LOTOS-EUROS v2.0), which allows the consideration of differences in the source attribution. We also compared the PM10 concentrations, and both models present satisfactory agreement in the 4 d forecasts of the surface concentrations, since the hourly concentrations can be highly correlated with in situ observations. The correlation coefficients reach values of up to 0.58 for LOTOS-EUROS and 0.50 for EMEP for the urban stations; the values are 0.58 for LOTOS-EUROS and 0.72 for EMEP for the rural stations. However, the models underpredict the highest hourly concentrations measured by the urban stations (mean underestimation of 36 %), which is to be expected given the relatively coarse model resolution used (0.25∘ longitude × 0.125∘ latitude). For the source attribution calculations, LOTOS-EUROS uses a labelling technique, while the EMEP/MSC-W model uses a scenario having reduced anthropogenic emissions, and then it is compared to a reference run where no changes are applied. Different percentages (5 %, 15 %, and 50 %) for the reduced emissions in the EMEP/MSC-W model were used to test the robustness of the methodology. The impact of the different ways to define the urban area for the studied cities was also investigated (i.e. one model grid cell, nine grid cells, and grid cells covering the definition given by the Global Administrative Areas – GADM). We found that the combination of a 15 % emission reduction and a larger domain (nine grid cells or GADM) helps to preserve the linearity between emission and concentrations changes. The nonlinearity, related to the emission reduction scenario used, is suggested by the nature of the mismatch between the total concentration and the sum of the concentrations from different calculated sources. Even limited, this nonlinearity is observed in the NO3-, NH4+, and H2O concentrations, which is related to gas–aerosol partitioning of the species. The use of a 15 % emission reduction and of a larger city domain also causes better agreement on the determination of the main country contributors between both country source calculations. Over the 34 European cities investigated, PM10 was dominated by domestic emissions for the studied episode (1–9 December 2016). The two models generally agree on the dominant external country contributor (68 % on an hourly basis) to PM10 concentrations. Overall, 75 % of the hourly predicted PM10 concentrations of both models have the same top five main country contributors. Better agreement on the dominant country contributor for primary (emitted) species (70 % is found for primary organic matter (POM) and 80 % for elemental carbon – EC) than for the inorganic secondary component of the aerosol (50 %), which is predictable due to the conceptual differences in the source attribution used by both models. The country contribution calculated by the scenario approach depends on the chemical regime, which largely impacts the secondary components, unlike the calculation using the labelling approach.

In the framework of the EURODELTA-Trends (EDT) modeling experiment, several chemical transport models (CTMs) were applied for the 1990–2010 period to investigate air quality changes in Europe as well as the capability of the models to reproduce observed long-term air quality trends. Five CTMs have provided modeled air quality data for 21 continuous years in Europe using emission scenarios prepared by the International Institute for Applied Systems Analysis/Greenhouse Gas – Air Pollution Interactions and Synergies (IIASA/GAINS) and corresponding year-by-year meteorology derived from ERA-Interim global reanalysis. For this study, long-term observations of particle sulfate (SO42-), total nitrate (TNO3), total ammonium (TNHx) as well as sulfur dioxide (SO2) and nitrogen dioxide (NO2) for multiple sites in Europe were used to evaluate the model results. The trend analysis was performed for the full 21 years (referred to as PT) but also for two 11-year subperiods: 1990–2000 (referred to as P1) and 2000–2010 (referred to as P2). The experiment revealed that the models were able to reproduce the faster decline in observed SO2 concentrations during the first decade, i.e., 1990–2000, with a 64 %–76 % mean relative reduction in SO2 concentrations indicated by the EDT experiment (range of all the models) versus an 82 % mean relative reduction in observed concentrations. During the second decade (P2), the models estimated a mean relative reduction in SO2 concentrations of about 34 %–54 %, which was also in line with that observed (47 %). Comparisons of observed and modeled NO2 trends revealed a mean relative decrease of 25 % and between 19 % and 23 % (range of all the models) during the P1 period, and 12 % and between 22 % and 26 % (range of all the models) during the P2 period, respectively. Comparisons of observed and modeled trends in SO42- concentrations during the P1 period indicated that the models were able to reproduce the observed trends at most of the sites, with a 42 %–54 % mean relative reduction indicated by the EDT experiment (range of all models) versus a 57 % mean relative reduction in observed concentrations and with good performance also during the P2 and PT periods, even though all the models overpredicted the number of statistically significant decreasing trends during the P2 period. Moreover, especially during the P1 period, both modeled and observational data indicated smaller reductions in SO42- concentrations compared with their gas-phase precursor (i.e., SO2), which could be mainly attributed to increased oxidant levels and pH-dependent cloud chemistry. An analysis of the trends in TNO3 concentrations indicated a 28 %–39 % and 29 % mean relative reduction in TNO3 concentrations for the full period for model data (range of all the models) and observations, respectively. Further analysis of the trends in modeled HNO3 and particle nitrate (NO3-) concentrations revealed that the relative reduction in HNO3 was larger than that for NO3- during the P1 period, which was mainly attributed to an increased availability of “free ammonia”. By contrast, trends in modeled HNO3 and NO3- concentrations were more comparable during the P2 period. Also, trends of TNHx concentrations were, in general, underpredicted by all models, with worse performance for the P1 period than for P2. Trends in modeled anthropogenic and biogenic secondary organic aerosol (ASOA and BSOA) concentrations together with the trends in available emissions of biogenic volatile organic compounds (BVOCs) were also investigated. A strong decrease in ASOA was indicated by all the models, following the reduction in anthropogenic non-methane VOC (NMVOC) precursors. Biogenic emission data provided by the modeling teams indicated a few areas with statistically significant increase in isoprene emissions and monoterpene emissions during the 1990–2010 period over Fennoscandia and eastern European regions (i.e., around 14 %–27 %), which was mainly attributed to the increase of surface temperature. However, the modeled BSOA concentrations did not linearly follow the increase in biogenic emissions. Finally, a comprehensive evaluation against positive matrix factorization (PMF) data, available during the second period (P2) at various European sites, revealed a systematic underestimation of the modeled SOA fractions of a factor of 3 to 11, on average, most likely because of missing SOA precursors and formation pathways, with reduced biases for the models that accounted for chemical aging of semi-volatile SOA components in the atmosphere.

The wet deposition of nitrogen and sulfur in Europe for the period 1990–2010 was estimated by six atmospheric chemistry transport models (CHIMERE, CMAQ, EMEP MSC-W, LOTOS-EUROS, MATCH and MINNI) within the framework of the EURODELTA-Trends model intercomparison. The simulated wet deposition and its trends for two 11-year periods (1990–2000 and 2000–2010) were evaluated using data from observations from the EMEP European monitoring network. For annual wet deposition of oxidised nitrogen (WNOx), model bias was within 30 % of the average of the observations for most models. There was a tendency for most models to underestimate annual wet deposition of reduced nitrogen (WNHx), although the model bias was within 40 % of the average of the observations. Model bias for WNHx was inversely correlated with model bias for atmospheric concentrations of NH3+NH4+, suggesting that an underestimation of wet deposition partially contributed to an overestimation of atmospheric concentrations. Model bias was also within about 40 % of the average of the observations for the annual wet deposition of sulfur (WSOx) for most models. Decreasing trends in WNOx were observed at most sites for both 11-year periods, with larger trends, on average, for the second period. The models also estimated predominantly decreasing trends at the monitoring sites and all but one of the models estimated larger trends, on average, for the second period. Decreasing trends were also observed at most sites for WNHx, although larger trends, on average, were observed for the first period. This pattern was not reproduced by the models, which estimated smaller decreasing trends, on average, than those observed or even small increasing trends. The largest observed trends were for WSOx, with decreasing trends at more than 80 % of the sites. On average, the observed trends were larger for the first period. All models were able to reproduce this pattern, although some models underestimated the trends (by up to a factor of 4) and others overestimated them (by up to 40 %), on average. These biases in modelled trends were directly related to the tendency of the models to under- or overestimate annual wet deposition and were smaller for the relative trends (expressed as % yr−1 relative to the deposition at the start of the period). The fact that model biases were fairly constant throughout the time series makes it possible to improve the predictions of wet deposition for future scenarios by adjusting the model estimates using a bias correction calculated from past observations. An analysis of the contributions of various factors to the modelled trends suggests that the predominantly decreasing trends in wet deposition are mostly due to reductions in emissions of the precursors NOx, NH3 and SOx. However, changes in meteorology (e.g. precipitation) and other (non-linear) interactions partially offset the decreasing trends due to emission reductions during the first period but not the second. This suggests that the emission reduction measures had a relatively larger effect on wet deposition during the second period, at least for the sites with observations.

The implementation of European emission abatement strategies has led to a significant reduction in the emissions of ozone precursors during the last decade. Ground-level ozone is also influenced by meteorological factors such as temperature, which exhibit interannual variability and are expected to change in the future. The impacts of climate change on air quality are usually investigated through air-quality models that simulate interactions between emissions, meteorology and chemistry. Within a multi-model assessment, this study aims to better understand how air-quality models represent the relationship between meteorological variables and surface ozone concentrations over Europe. A multiple linear regression (MLR) approach is applied to observed and modelled time series across 10 European regions in springtime and summertime for the period of 2000–2010 for both models and observations. Overall, the air-quality models are in better agreement with observations in summertime than in springtime and particularly in certain regions, such as France, central Europe or eastern Europe, where local meteorological variables show a strong influence on surface ozone concentrations. Larger discrepancies are found for the southern regions, such as the Balkans, the Iberian Peninsula and the Mediterranean basin, especially in springtime. We show that the air-quality models do not properly reproduce the sensitivity of surface ozone to some of the main meteorological drivers, such as maximum temperature, relative humidity and surface solar radiation. Specifically, all air-quality models show more limitations in capturing the strength of the ozone–relative-humidity relationship detected in the observed time series in most of the regions, for both seasons. Here, we speculate that dry-deposition schemes in the air-quality models might play an essential role in capturing this relationship. We further quantify the relationship between ozone and maximum temperature (mo3 − T, climate penalty) in observations and air-quality models. In summertime, most of the air-quality models are able to reproduce the observed climate penalty reasonably well in certain regions such as France, central Europe and northern Italy. However, larger discrepancies are found in springtime, where air-quality models tend to overestimate the magnitude of the observed climate penalty.

Eleven of the world's 20 most polluted cities are located in India and poor air quality is already a major public health issue. However, anthropogenic emissions are predicted to increase substantially in the short-term (2030) and medium-term (2050) futures in India, especially if no further policy efforts are made. In this study, the EMEP/MSC-W chemical transport model has been used to predict changes in surface ozone (O3) and fine particulate matter (PM2.5) for India in a world of changing emissions and climate. The reference scenario (for present-day) is evaluated against surface-based measurements, mainly at urban stations. The evaluation has also been extended to other data sets which are publicly available on the web but without quality assurance. The evaluation shows high temporal correlation for O3 (r = 0.9) and high spatial correlation for PM2.5 (r = 0.5 and r = 0.8 depending on the data set) between the model results and observations. While the overall bias in PM2.5 is small (lower than 6 %), the model overestimates O3 by 35 %. The underestimation in NOx titration is probably the main reason for the O3 overestimation in the model. However, the level of agreement can be considered satisfactory in this case of a regional model being evaluated against mainly urban measurements, and given the inevitable uncertainties in much of the input data.For the 2050s, the model predicts that climate change will have distinct effects in India in terms of O3 pollution, with a region in the north characterized by a statistically significant increase by up to 4 % (2 ppb) and one in the south by a decrease up to −3 % (−1.4 ppb). This variation in O3 is assumed to be partly related to changes in O3 deposition velocity caused by changes in soil moisture and, over a few areas, partly also by changes in biogenic non-methane volatile organic compounds.Our calculations suggest that PM2.5 will increase by up to 6.5 % over the Indo-Gangetic Plain by the 2050s. The increase over India is driven by increases in dust, particulate organic matter (OM) and secondary inorganic aerosols (SIAs), which are mainly affected by the change in precipitation, biogenic emissions and wind speed.The large increase in anthropogenic emissions has a larger impact than climate change, causing O3 and PM2.5 levels to increase by 13 and 67 % on average in the 2050s over the main part of India, respectively. By the 2030s, secondary inorganic aerosol is predicted to become the second largest contributor to PM2.5 in India, and the largest in the 2050s, exceeding OM and dust.

The EURODELTA-Trends multi-model chemistry-transport experiment has been designed to facilitate a better understanding of the evolution of air pollution and its drivers for the period 1990–2010 in Europe. The main objective of the experiment is to assess the efficiency of air pollutant emissions mitigation measures in improving regional-scale air quality. The present paper formulates the main scientific questions and policy issues being addressed by the EURODELTA-Trends modelling experiment with an emphasis on how the design and technical features of the modelling experiment answer these questions. The experiment is designed in three tiers, with increasing degrees of computational demand in order to facilitate the participation of as many modelling teams as possible. The basic experiment consists of simulations for the years 1990, 2000, and 2010. Sensitivity analysis for the same three years using various combinations of (i) anthropogenic emissions, (ii) chemical boundary conditions, and (iii) meteorology complements it. The most demanding tier consists of two complete time series from 1990 to 2010, simulated using either time-varying emissions for corresponding years or constant emissions. Eight chemistry-transport models have contributed with calculation results to at least one experiment tier, and five models have – to date – completed the full set of simulations (and 21-year trend calculations have been performed by four models). The modelling results are publicly available for further use by the scientific community. The main expected outcomes are (i) an evaluation of the models' performances for the three reference years, (ii) an evaluation of the skill of the models in capturing observed air pollution trends for the 1990–2010 time period, (iii) attribution analyses of the respective role of driving factors (e.g. emissions, boundary conditions, meteorology), (iv) a dataset based on a multi-model approach, to provide more robust model results for use in impact studies related to human health, ecosystem, and radiative forcing.

This paper presents a new version of the EMEP MSC-W model called eEMEP developed for transportation and dispersion of volcanic emissions, both gases and ash. EMEP MSC-W is usually applied to study problems with air pollution and aerosol transport and requires some adaptation to treat volcanic eruption sources and effluent dispersion. The operational set-up of model simulations in case of a volcanic eruption is described. Important choices have to be made to achieve CPU efficiency so that emergency situations can be tackled in time, answering relevant questions of ash advisory authorities. An efficient model needs to balance the complexity of the model and resolution. We have investigated here a meteorological uncertainty component of the volcanic cloud forecast by using a consistent ensemble meteorological dataset (GLAMEPS forecast) at three resolutions for the case of SO2 emissions from the 2014 Barðarbunga eruption. The low resolution (40 × 40 km) ensemble members show larger agreement in plume position and intensity, suggesting that the ensemble here does not give much added value. To compare the dispersion at different resolutions, we compute the area where the column load of the volcanic tracer, here SO2, is above a certain threshold, varied for testing purposes between 0.25 and 50 Dobson units. The increased numerical diffusion causes a larger area (+34 %) to be covered by the volcanic tracer in the low resolution simulations than in the high resolution ones. The higher resolution (10 × 10 km) ensemble members show higher column loads farther away from the volcanic eruption site in narrower clouds. Cloud positions are more varied between the high resolution members, and the cloud forms resemble the observed clouds more than the low resolution ones. For a volcanic emergency case this means that to obtain quickly results of the transport of volcanic emissions, an individual simulation with our low resolution is sufficient; however, to forecast peak concentrations with more certainty for forecast or scientific analysis purposes, a finer resolution is needed. The model is further developed to simulate ash from highly explosive eruptions. A possibility of increasing the number of vertical layers, achieving finer vertical resolution, as well as a higher model top, is included in the eEMEP version. Ash size distributions may be altered for different volcanic eruptions and assumptions. Since ash particles are larger than typical particles in the standard model, gravitational settling across all vertical layers is included. We attempt finally a specific validation of the simulation of ash and its vertical distribution. Model simulations with and without gravitational settling for the 2010 Eyjafjallajökull eruption are compared to lidar observations over central Europe. The results show that with gravitation the centre of the ash mass can be 1 km lower over central Europe than without gravitation. However, the height variations in the ash layer caused by real weather situations are not captured perfectly well by either of the two simulations, playing down the role of gravitation parameterization imperfections. Both model simulations have on average an ash centre of mass below the observed values. Correlations between the observed and corresponding model centres of mass are higher for the model simulation with gravitational settling for four of the six stations studied here. The inclusion of gravitational settling is suggested to be required for a volcanic ash model.

The EURODELTA III exercise has facilitated a comprehensive intercomparison and evaluation of chemistry transport model performances. Participating models performed calculations for four 1-month periods in different seasons in the years 2006 to 2009, allowing the influence of different meteorological conditions on model performances to be evaluated. The exercise was performed with strict requirements for the input data, with few exceptions. As a consequence, most of differences in the outputs will be attributed to the differences in model formulations of chemical and physical processes. The models were evaluated mainly for background rural stations in Europe. The performance was assessed in terms of bias, root mean square error and correlation with respect to the concentrations of air pollutants (NO2, O3, SO2, PM10 and PM2.5), as well as key meteorological variables. Though most of meteorological parameters were prescribed, some variables like the planetary boundary layer (PBL) height and the vertical diffusion coefficient were derived in the model preprocessors and can partly explain the spread in model results. In general, the daytime PBL height is underestimated by all models. The largest variability of predicted PBL is observed over the ocean and seas. For ozone, this study shows the importance of proper boundary conditions for accurate model calculations and then on the regime of the gas and particle chemistry. The models show similar and quite good performance for nitrogen dioxide, whereas they struggle to accurately reproduce measured sulfur dioxide concentrations (for which the agreement with observations is the poorest). In general, the models provide a close-to-observations map of particulate matter (PM2.5 and PM10) concentrations over Europe rather with correlations in the range 0.4–0.7 and a systematic underestimation reaching −10 µg m−3 for PM10. The highest concentrations are much more underestimated, particularly in wintertime. Further evaluation of the mean diurnal cycles of PM reveals a general model tendency to overestimate the effect of the PBL height rise on PM levels in the morning, while the intensity of afternoon chemistry leads formation of secondary species to be underestimated. This results in larger modelled PM diurnal variations than the observations for all seasons. The models tend to be too sensitive to the daily variation of the PBL. All in all, in most cases model performances are more influenced by the model setup than the season. The good representation of temporal evolution of wind speed is the most responsible for models' skillfulness in reproducing the daily variability of pollutant concentrations (e.g. the development of peak episodes), while the reconstruction of the PBL diurnal cycle seems to play a larger role in driving the corresponding pollutant diurnal cycle and hence determines the presence of systematic positive and negative biases detectable on daily basis.

The volcanic fissure at Holuhraun, Iceland started at the end of August 2014 and continued for 6 months to the end of February 2015, with an extensive lava flow onto the Holuhraun plain. This event was associated with large SO2 emissions, amounting up to approximately 4.5 times the daily anthropogenic SO2 emitted from the 28 European Union countries, Norway, Switzerland and Iceland. In this paper we present results from EMEP/MSC-W model simulations to which we added 750 kg s−1 SO2 emissions at the Holuhraun plain from September to November (SON), testing three different emission heights. The three simulated SO2 concentrations, weighted with the OMI (Ozone Monitoring Instrument) satellite averaging kernel, are found to be within 30 % of the satellite-observed SO2 column burden. Constraining the SO2 column burden with the satellite data while using the kernel along with the three simulated height distributions of SO2, we estimate that the median of the daily burdens may have been between 13 and 40 kt in the North Atlantic area under investigation. We suggest this to be the uncertainty in the satellite-derived burdens of SO2, mainly due to the unknown vertical distribution of SO2. Surface observations in Europe outside Iceland showed concentration increases up to > 500 µg m−3 SO2 from volcanic plumes passing. Three well identified episodes, where the plume crossed several countries, are compared in detail to surface measurements. For all events, the general timing of the observed concentration peaks compared quite well to the model results. The overall changes to the European SO2 budget due to the volcanic fissure are estimated. Three-monthly wet deposition (SON) of SOx in the 28 European Union countries, Norway and Switzerland is found to be more than 30 % higher in the model simulation with Holuhraun emissions compared to a model simulation with no Holuhraun emissions. The largest increases, apart from extreme values on Iceland, are found on the coast of northern Norway, a region with frequent precipitation during westerly winds. Over a 3-month average (during SON 2014) over Europe, SO2 and PM2.5 surface concentrations, due to the volcanic emissions, increased by only ten and 6 % respectively. Although the percent increase of PM2.5 concentration is highest over Scandinavia and Scotland, an increase in PM exceedance days is found over Ireland and the already polluted Benelux region (up to 3 additional days), where any small increase in particulate matter concentration leads to an increase in exceedance days.

Despite increasing emission controls, particulate matter (PM) has remained a critical issue for European air quality in recent years. The various sources of PM, both from primary particulate emissions as well as secondary formation from precursor gases, make this a complex problem to tackle. In order to allow for credible predictions of future concentrations under policy assumptions, a modelling approach is needed that considers all chemical processes and spatial dimensions involved, from long-range transport of pollution to local emissions in street canyons. Here we describe a modelling scheme which has been implemented in the GAINS integrated assessment model to assess compliance with PM10 (PM with aerodynamic diameter 10 across Europe. Furthermore, we analyse the predicted evolution of PM10 concentrations in the European Union until 2030 under different policy scenarios. Significant improvements in ambient PM10 concentrations are expected assuming successful implementation of already agreed legislation; however, these will not be large enough to ensure attainment of PM10 limit values in hot spot locations such as Southern Poland and major European cities. Remaining issues are largely eliminated in a scenario applying the best available emission control technologies to the maximal technically feasible extent.

The first EMEP intensive measurement periods were held in June 2006 and January 2007. The measurements aimed to characterize the aerosol chemical compositions, including the gas/aerosol partitioning of inorganic compounds. The measurement program during these periods included daily or hourly measurements of the secondary inorganic components, with additional measurements of elemental- and organic carbon (EC and OC) and mineral dust in PM1, PM2.5 and PM10. These measurements have provided extended knowledge regarding the composition of particulate matter and the temporal and spatial variability of PM, as well as an extended database for the assessment of chemical transport models. This paper summarise the first experiences of making use of measurements from the first EMEP intensive measurement periods along with EMEP model results from the updated model version to characterise aerosol composition. We investigated how the PM chemical composition varies between the summer and the winter month and geographically. The observation and model data are in general agreement regarding the main features of PM10 and PM2.5 composition and the relative contribution of different components, though the EMEP model tends to give slightly lower estimates of PM10 and PM2.5 compared to measurements. The intensive measurement data has identified areas where improvements are needed. Hourly concurrent measurements of gaseous and particulate components for the first time facilitated testing of modelled diurnal variability of the gas/aerosol partitioning of nitrogen species. In general, the modelled diurnal cycles of nitrate and ammonium aerosols are in fair agreement with the measurements, but the diurnal variability of ammonia is not well captured. The largest differences between model and observations of aerosol mass are seen in Italy during winter, which to a large extent may be explained by an underestimation of residential wood burning sources. It should be noted that both primary and secondary OC has been included in the calculations for the first time, showing promising results. Mineral dust is important, especially in southern Europe, and the model seems to capture the dust episodes well. The lack of measurements of mineral dust hampers the possibility for model evaluation for this highly uncertain PM component. There are also lessons learnt regarding improved measurements for future intensive periods. There is a need for increased comparability between the measurements at different sites. For the nitrogen compounds it is clear that more measurements using artefact free methods based on continuous measurement methods and/or denuders are needed. For EC/OC, a reference methodology (both in field and laboratory) was lacking during these periods giving problems with comparability, though measurement protocols have recently been established and these should be followed by the Parties to the EMEP Protocol. For measurements with no defined protocols, it might be a good solution to use centralised laboratories to ensure comparability across the network. To cope with the introduction of these new measurements, new reporting guidelines have been developed to ensure that all proper information about the methodologies and data quality is given.

The Meteorological Synthesizing Centre-West (MSC-W) of the European Monitoring and Evaluation Programme (EMEP) has been performing model calculations in support of the Convention on Long Range Transboundary Air Pollution (CLRTAP) for more than 30 years. The EMEP MSC-W chemical transport model is still one of the key tools within European air pollution policy assessments. Traditionally, the model has covered all of Europe with a resolution of about 50 km × 50 km, and extending vertically from ground level to the tropopause (100 hPa). The model has changed extensively over the last ten years, however, with flexible processing of chemical schemes, meteorological inputs, and with nesting capability: the code is now applied on scales ranging from local (ca. 5 km grid size) to global (with 1 degree resolution). The model is used to simulate photo-oxidants and both inorganic and organic aerosols. In 2008 the EMEP model was released for the first time as public domain code, along with all required input data for model runs for one year. The second release of the EMEP MSC-W model became available in mid 2011, and a new release is targeted for summer 2012. This publication is intended to document this third release of the EMEP MSC-W model. The model formulations are given, along with details of input data-sets which are used, and a brief background on some of the choices made in the formulation is presented. The model code itself is available at www.emep.int, along with the data required to run for a full year over Europe.

The EMEP/MSC-W model has been used to compute atmospheric nitrogen deposition into the Baltic Sea basin for the period of 12 yr: 1995–2006. The level of annual total nitrogen deposition into the Baltic Sea basin has changed from 230 Gg N in 1995 to 199 Gg N in 2006, decreasing 13 %. This value corresponds well with the total nitrogen emission reduction (11 %) in the HELCOM Contracting Parties. However, inter-annual variability of nitrogen deposition to the Baltic Sea basin is relatively large, ranging from −13 % to +17 % of the averaged value. It is mainly caused by the changing meteorological conditions and especially precipitation in the considered period. The calculated monthly deposition pattern is similar for most of the years showing maxima in the autumn months October and November. The source allocation budget for atmospheric nitrogen deposition to the Baltic Sea basin was calculated for each year of the period 1997–2006. The main emission sources contributing to total nitrogen deposition are: Germany 18–22 %, Poland 11–13 % and Denmark 8–11 %. There is also a significant contribution from distant sources like the United Kingdom 6–9 %, as well as from the international ship traffic on the Baltic Sea 4–5 %.

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.

This paper introduces two changes of the turbulence parameterization for the EMEP (European Monitoring and Evaluation Programme) Eulerian air pollution model: the replacement of the Blackadar in stable and O'Brien in unstable turbulence formulations with an analytical vertical diffusion profile (K(z)) called Grisogono, and a different mixing height determination, based on a bulk Richardson number formulation (RiB). The operational or standard (STD) and proposed new parameterization for eddy diffusivity have been validated in all stability conditions against the observed daily surface nitrogen dioxide (NO2), sulphur dioxide (SO2) and sulphate (SO42−) concentrations at different EMEP stations during the year 2001. A moderate improvement in the correlation coefficient and bias for NO2 and SO2 and a slight improvement for sulphate is found for the most of the analyzed stations with the Grisogono K(z) scheme, which is recommended for further application due to its scientific and technical advantages. The newly extended approach for the mechanical eddy diffusivity is applied to the Large Eddy Simulation data focusing at the bulk properties of the neutral and stable atmospheric boundary layer. A summary and extension of the previous work on the empirical coefficients in neutral and stable conditions is provided with the recommendations to the further model development. Special emphasis is given to the representation of the ABL in order to capture the vertical transport and dispersion of the atmospheric air pollution. Two different schemes for the ABL height determination are evaluated against the radiosounding data in January and July 2001, and against the data from the Cabauw tower, the Netherlands, for the same year. The validation of the ABL parameterizations has shown that the EMEP model is able to reproduce spatial and temporal mixing height variability. Improvements are identified especially in stable conditions with the new ABL height scheme based on the RiB number.

During the last twenty-five years European emission data have been compiled and reported under the Cooperative Programme for Monitoring and Evaluation of the Long-range Transmission of Air Pollutants in Europe (EMEP) as part of the work under the UNECE Convention on Long-range Transboundary Air Pollution (LRTAP). This paper presents emission trends of SO2 reported to EMEP and validated within the programme for the period 1980–2004. These European anthropogenic sulphur emissions have been steadily decreasing over the last twenty-five years, amounting from about 55 Tg SO2 in 1980 to 15 Tg SO2 in 2004. The uncertainty in sulphur emission estimates for individual countries and years are documented to range between 3% and 25%. The relative contribution of European emissions to global anthropogenic sulphur emissions has been halved during this period. Based on annual emission reports from European countries, three emission reduction regimes have been identified. The period 1980–1989 is characterized by low annual emission reductions (below 5% reduction per year and 20% for the whole period) and is dominated by emission reductions in Western Europe. The period 1990–1999 is characterised by high annual emission reductions (up to 11% reduction per year and 54% for the whole period), most pronounced in Central and Eastern Europe. The annual emission reductions in the period 2000–2004 are medium to low (below 6% reduction per year and 17% for the whole period) and reflect the unified Europe, with equally large reductions in both East and West. The sulphur emission reduction has been largest in the sector Combustion in energy and transformation industries, but substantial decreases are also seen in the Non-industrial combustion plants together with the sectors Industrial combustion and Industrial production processes. The majority of European countries have reduced their emissions by more than 60% between 1990 and 2004, and one quarter have already achieved sulphur emission reductions higher than 80%. At European level, the total sulphur target for 2010 set in the Gothenburg Protocol (16 Tg) has apparently already been met by 2004. However, still half of the Parties to the Gothenburg Protocol have to reduce further their sulphur emissions in order to attain their individual country total emission targets for 2010. It is also noteworthy that, contrasting the Gothenburg Protocol requirements, a growing number of countries have recently been reporting increasing sulphur emissions, while others report only minor further decreases. The emission trends presented here are supported by different studies of air concentrations and depositions carried out within and outside the framework of the LRTAP Convention.

Ozone levels in Europe are changing. Emissions of ozone precursors from Europe (NOx, CO and non-methane hydrocarbons) have been substantially reduced over the last 10–15 years, but changes in ozone levels cannot be explained by changes in European emissions alone. The observed ozone trends at many European sites are only partially reproduced by global or regional photochemistry models, and possible reasons for this are discussed. In order to further explain the European trends in ozone since 1990, the EMEP regional photochemistry model has been run for the years 1990 and 1995–2002. The EMEP model is a regional model centred over Europe but the model domain also includes most of the North Atlantic and the polar region. Climatological ozone data are used as initial and lateral boundary concentrations. Model results are compared to measurements over this timespan of 12 years. Possible causes for the measured trends in European surface ozone have been investigated using model sensitivity runs perturbing emissions and lateral boundary concentrations. The increase in winter ozone partially, and the decrease in the magnitude of high ozone episodes, is attributed to the decrease in ozone precursor emissions since 1990 by the model. Furthermore, the model calculations indicate that the emission reductions have resulted in a marked decrease in summer ozone in major parts of Europe, in particular in Germany. Such a trend in summer ozone is likely to be difficult to identify from the measurements alone because of large inter-annual variability.

The EMEP MSC-W Eulerian chemical transport model, and its predictions of deposition of acidifying and eutrophying pollutants over Europe, play a key role in the development of emission control strategies for Europe. It is important that this model is tested against observational data. Here we compare the results of the EMEP model with measured data from 160 sites of the European Union/ICP Forest (Level II) monitoring network, for the years 1997 and 2000. This comparison comprises: (a) Precipitation amount, (b) Total deposition of SO2−4 to coniferous and deciduous forests, (c) Wet deposition of SO2−4, NO3− and NH4+ in open field sites, and (d) Concentrations of SO2−4, NO3− and NH4+ in precipitation. Concerning precipitation, the EMEP model and ICP network showed very similar overall levels (within 4% for 1997 and 11% for 2000). The correlation was, however, poor (r2=0.15–0.23). This can be attributed largely to the influence of a few outliers, combined with a small range of rainfall amounts for most points. Correlations between modelled and observed deposition values in this study were rather high (r2 values between 0.4–0.8 for most components and years), with mean values across all sites being within 30%. The EMEP model tends to give somewhat lower values for SO2−4, NO3− and NH4+ wet deposition to ICP, but differences in mean values were within 20% in 1997 and 30% in 2000. Modelled and observed concentrations of SO2−4, NO3− and NH4+ in precipitation are very similar on average (differences of 0–14%), with good correlation between modelled and observed data (r2=0.50–0.78). Differences between the EMEP model and ICP measurements are thought to arise from a mixture of problems with both the observations and model. However, the overall conclusion is that the EMEP model performs rather well in reproducing patterns of S and N deposition to European forests.

Over the last decades, energy and pollution control policies combined with structural changes in the economy decoupled emission trends from economic growth, increasingly also in the developing world. It is found that effective implementation of the presently decided national pollution control regulations should allow further economic growth without major deterioration of ambient air quality, but will not be enough to reduce pollution levels in many world regions. A combination of ambitious policies focusing on pollution controls, energy and climate, agricultural production systems and addressing human consumption habits could drastically improve air quality throughout the world. By 2040, mean population exposure to PM2.5 from anthropogenic sources could be reduced by about 75% relative to 2015 and brought well below the WHO guideline in large areas of the world. While the implementation of the proposed technical measures is likely to be technically feasible in the future, the transformative changes of current practices will require strong political will, supported by a full appreciation of the multiple benefits. Improved air quality would avoid a large share of the current 3-9 million cases of premature deaths annually. At the same time, the measures that deliver clean air would also significantly reduce emissions of greenhouse gases and contribute to multiple UN sustainable development goals. This article is part of a discussion meeting issue 'Air quality, past present and future'.

The profound changes in global SO 2 emissions over the last decades have affected atmospheric composition on a regional and global scale with large impact on air quality, atmospheric deposition and the radiative forcing of sulfate aerosols. Reproduction of historical atmospheric pollution levels based on global aerosol models and emission changes is crucial to prove that such models are able to predict future scenarios. Here, we analyze consistency of trends in observations of sulfur components in air and precipitation from major regional networks and estimates from six different global aerosol models from 1990 until 2015. There are large interregional differences in the sulfur trends consistently captured by the models and observations, especially for North America and Europe. Europe had the largest reductions in sulfur emissions in the first part of the period while the highest reduction came later in North America and East Asia. The uncertainties in both the emissions and the representativity of the observations are larger in Asia. However, emissions from East Asia clearly increased from 2000 to 2005 followed by a decrease, while in India a steady increase over the whole period has been observed and modelled. The agreement between a bottom-up approach, which uses emissions and process-based chemical transport models, with independent observations gives an improved confidence in the understanding of the atmospheric sulfur budget.

Background: This paper aims to investigate the correlations between the concentrations of nine heavy metals in moss and atmospheric deposition within ecological land classes covering Europe. Additionally, it is examined to what extent the statistical relations are affected by the land use around the moss sampling sites. Based on moss data collected in 2010/2011 throughout Europe and data on total atmospheric deposition modelled by two chemical transport models (EMEP MSC-E, LOTOS-EUROS), correlation coefficients between concentrations of heavy metals in moss and in modelled atmospheric deposition were specified for spatial subsamples defined by ecological land classes of Europe (ELCE) as a spatial reference system. Linear discriminant analysis (LDA) and logistic regression (LR) were then used to separate moss sampling sites regarding their contribution to the strength of correlation considering the areal percentage of urban, agricultural and forestry land use around the sampling location. After verification LDA models by LR, LDA models were used to transform spatial information on the land use to maps of potential correlation levels, applicable for future network planning in the European Moss Survey., Results: Correlations between concentrations of heavy metals in moss and in modelled atmospheric deposition were found to be specific for elements and ELCE units. Land use around the sampling sites mainly influences the correlation level. Small radiuses around the sampling sites examined (5 km) are more relevant for Cd, Cu, Ni, and Zn, while the areal percentage of urban and agricultural land use within large radiuses (75-100 km) is more relevant for As, Cr, Hg, Pb, and V. Most valid LDA models pattern with error rates of < 40% were found for As, Cr, Cu, Hg, Pb, and V. Land use-dependent predictions of spatial patterns split up Europe into investigation areas revealing potentially high (= above-average) or low (= below-average) correlation coefficients., Conclusions: LDA is an eligible method identifying and ranking boundary conditions of correlations between atmospheric deposition and respective concentrations of heavy metals in moss and related mapping considering the influence of the land use around moss sampling sites.

Concerning increased degradation of marine ecosystems, there is a great political and institutional demand for an array of different tools to restore a good environmental status. Thereby, eutrophication is acknowledged as one of the major human induced stressors which has to be monitored and reduced. The present study concentrates on an assessment of the eutrophication status of the Baltic Sea Protected Areas by use of available data and GIS technologies. Two geodata layers were used for analysis: (1) a map on the eutrophication status of the Baltic Sea generated by the Helsinki Commission applying the HELCOM Eutrophication Assessment Tool (HEAT), and (2) modelled data on atmospheric nitrogen deposition made available by the European Monitoring and Evaluation Programme (EMEP). The results yielded comprehensive and conclusive data indicating that most of the BSPAs may be classified as being 'affected by eutrophication' and underlining the need to decrease the overall emissions of nutrients., (Copyright © 2011 Elsevier Ltd. All rights reserved.)

We analyze trends of some nitrogen compounds using long-term measurements and results from the EMEP (co-operative programme for monitoring and evaluation of the long-range transmissions of air pollutants in Europe) chemical transport model at EMEP sites. We find statistically significant declines at the majority of sites for NH(x) (sum of ammonia and ammonium) in air and for nitrate and ammonium in precipitation, but only at a few sites for xNO3 (sum of nitrate and nitric acid) in air. Model calculations and measurements give similar results. We demonstrate that the lack of trends for xNO3 in air at least partly can be attributed to a shift in the equilibrium between nitric acid and ammonium nitrate towards particulate phase, caused by reductions in the sulfur dioxide emissions.

Doublet bands of NbO in the near infrared region have been observed in emission with FTS techniques using an electrodeless 2450 MHz discharge as a source. Transitions involving the vibrational levels v = 0-4 of a low-lying a2Delta state of configuration sigma2delta and four additional doublet states (c2Pi, d2Deltai, e2Phi, and f2Pii) have been recorded at high resolution. Furthermore, a 2Sigma state, assigned as b2Sigma-, has been observed through the c2Pi (v = 0) --> b2Sigma- (v = 0, 1) transitions in the 1.6 &mgr;m region. Rotational analyses of the doublet bands have been performed. Most of the excited doublet states lie only slightly above or below the well-known B4Pi state. The density of states is fairly high immediately above B4Pi, and characterizations of some of the states in this region involve difficulties. A currently unanalyzed band, centered at 11 820 cm-1, has been preliminarily attributed to the A4Pi --> X4Sigma- (0, 0) transition. Nuclear hyperfine effects are barely detectable in orbitally degenerate states of the doublet manifold at Doppler-limited resolution, while the b2Sigma- state of configuration sigmadelta2 shows partly resolved magnetic hyperfine structure (b = -0.08191 cm-1). Large-scale all-electron CI calculations have been performed on doublet and quartet manifolds of NbO up to 22 000 cm-1. The calculations have been performed in two steps. In the first step, the spin-orbit effects within electronic states were not considered. An excellent overall agreement with experimental energies was obtained, except for the d2Deltai state. In the second step, all spin-orbit interactions were included. Also these calculations resulted in a good agreement with the experimental observations. The calculations also predict three hitherto unobserved low-lying states: 4Phi at 8545 cm-1, 2Gamma at 8430 cm-1 and 2Sigma+ at 9648 cm-1. Copyright 1997 Academic Press. Copyright 1997Academic Press