In this study, we evaluated three conceptually similar ozone gas deposition models. These dry deposition models are frequently used with chemical transport models for calculations over large spatial domains. However, large scale applications of surface-atmosphere exchange of reactive gases require modeling results as accurate as possible to avoid nonlinear accumulation of errors in the spatially representative results. In this paper, model evaluation and comparison against measured data over a coniferous forest at Niwot Ridge AmeriFlux site (Colorado, USA) is carried out. At this site, no previous model calibration took place for any of the models, therefore, we can test and compare their performances under similar conditions as they would perform in a spatial application. Our results show systematic model errors in all the three cases, model performance varies with time of the day, and the errors show a pronounced seasonal pattern as well. The introduction of soil moisture content stress in the model improved model performance regarding the magnitude of fluxes, but the correlation between measured and modeled ozone deposition values remains low. Our results suggest that ozone dry deposition model results should be interpreted carefully in large scale applications, where the accuracy can vary with land cover sometimes are biased.

s W al te r Se id lin g W al te r Se id lin g Air pollution, climate change and forest ecosystems: evidence for effects, adaptation, and mitigation W al te r Se id lin g Air pollution, climate change and forest ecosystems: evidence for effects, adaptation, and mitigation 6 th ICP Forests Scientific Conference 16–17 May 2017 – Bucharest/Romania

Earth system modelling will be the kind of modelling that will be performed more and more. After some philosophical remarks, an overview will be given of some science questions that can only be properly treated by earth system models. The focus of these science questions will be on emissions. Concerning meteorology, the problems still existing with the atmospheric boundary layer will be presented. Data-assimilation will be addressed as an application issue, which can only be carried out more objectively with earth system models. The paper ends with ten rules for correct modelling.

In the past few years a growing amount of space observations focusing on atmospheric composition has become available and this trend will continue with the launch of new satellites (ESA-Sentinels, NASA-TEMPO and JAXA air quality and climate mission) in the near future. To justify the production and launch of these expensive instruments, there is a need for determining the added value of future satellite instruments and their optimal design in an objective way. One methodology that can do so is the OSSE (Observing System Simulation Experiment). Although extensively used in the meteorological community, it’s use in the field of air quality and climate is still limited and a common approach is desirable. Based on existing studies and experience in the meteorological community we have identified requirements for each of the OSSE elements for performing a realistic OSSE. Using illustrative examples from existing air quality OSSEs we will present the methodology and the requirements for the application of OSSEs to satellite observations of atmospheric composition.

In this study we present a dynamic model evaluation of chemistry transport model LOTOS-EUROS (LOng Term Ozone Simulation – EURopean Operational Smog) to analyse the ability of the model to reproduce observed non-linear responses to emission changes and interannual variability of secondary inorganic aerosol (SIA) and its precursors over Europe from 1990 to 2009. The 20 year simulation was performed using a consistent set of meteorological data provided by RACMO2 (Regional Atmospheric Climate MOdel). Observations at European rural background sites have been used as a reference for the model evaluation. To ensure the consistency of the used observational data, stringent selection criteria were applied, including a comprehensive visual screening to remove suspicious data from the analysis. The LOTOS-EUROS model was able to capture a large part of the seasonal and interannual variability of SIA and its precursors' concentrations. The dynamic evaluation has shown that the model is able to simulate the declining trends observed for all considered sulfur and nitrogen components following the implementation of emission abatement strategies for SIA precursors over Europe. Both the observations and the model show the largest part of the decline in the 1990s, while smaller concentration changes and an increasing number of non-significant trends are observed and modelled between 2000 and 2009. Furthermore, the results confirm former studies showing that the observed trends in sulfate and total nitrate concentrations from 1990 to 2009 are lower than the trends in precursor emissions and precursor concentrations. The model captured well these non-linear responses to the emission changes. Using the LOTOS-EUROS source apportionment module, trends in the formation efficiency of SIA have been quantified for four European regions. The exercise has revealed a 20–50% more efficient sulfate formation in 2009 compared to 1990 and an up to 20% more efficient nitrate formation per unit nitrogen oxide emission, which added to the explanation of the non-linear responses. However, we have also identified some weaknesses in the model and the input data. LOTOS-EUROS underestimates the observed nitrogen dioxide concentrations throughout the whole time period, while it overestimates the observed nitrogen dioxide concentration trends. Moreover, model results suggest that the emission information of the early 1990s used in this study needs to be improved concerning magnitude and spatial distribution.

An attempt has been made by a combination of theory, observations, and especially modeling to determine the concentrations of trace gases and aerosols in the troposphere, without the influence of human beings.

In this study we investigate the ability of the Chemistry Transport Model (CTM) LOTOS-EUROS to explain the observed decrease in secondary inorganic aerosol (SIA) and its precursors between 1990 and 2009 over Europe. The model explicitly accounts for cloud chemistry and aerosol thermodynamics. The results have shown that the model largely captures the observed trends in SIA and its precursors’ concentrations while it underestimates the interannual variability. Using a source-apportionment module the amount of SIA formed per unit emission was traced for a number of regions. The results show 20–50 % more efficient SO4 2− formation in 2009 compared to 1990, whereas the change in NO3 − formation per unit NOx emission is lower (−10 % to +20 %) for the same time period.

The differences between air quality in urban and rural regions has been investigated for the current situation using both observations and modeling and also for future climate conditions

In this study the sensitivity of the model performance of the chemistry transport model (CTM) LOTOS-EUROS to the description of the temporal variability of emissions was investigated. Currently the temporal release of anthropogenic emissions is described by European average diurnal, weekly and seasonal time profiles per sector. These default time profiles largely neglect the variation of emission strength with activity patterns, region, species, emission process and meteorology. The three sources dealt with in this study are combustion in energy and transformation industries (SNAP1), nonindustrial combustion (SNAP2) and road transport (SNAP7). First of all, the impact of neglecting the temporal emission profiles for these SNAP categories on simulated concentrations was explored. In a second step, we constructed more detailed emission time profiles for the three categories and quantified their impact on the model performance both separately as well as combined. The performance in comparison to observations for Germany was quantified for the pollutants NO2, SO2 and PM10 and compared to a simulation using the default LOTOS-EUROS emission time profiles. The LOTOS-EUROS simulations were performed for the year 2006 with a temporal resolution of 1 h and a horizontal resolution of approximately 25 × 25km2. In general the largest impact on the model performance was found when neglecting the default time profiles for the three categories. The daily average correlation coefficient for instance decreased by 0.04 (NO2), 0.11 (SO2) and 0.01 (PM10) at German urban background stations compared to the default simulation. A systematic increase in the correlation coefficient is found when using the new time profiles. The size of the increase depends on the source category, component and station. Using national profiles for road transport showed important improvements in the explained variability over the weekdays as well as the diurnal cycle for NO2. The largest impact of the SNAP1 and 2 profiles were found for SO2. When using all new time profiles simultaneously in one simulation, the daily average correlation coefficient increased by 0.05 (NO2), 0.07 (SO2) and 0.03 (PM10) at urban background stations in Germany. This exercise showed that to improve the performance of a CTM, a better representation of the distribution of anthropogenic emission in time is recommendable. This can be done by developing a dynamical emission model that takes into account regional specific factors and meteorology.

Air pollution is associated with adverse effects on human health through exposure to PM and ozone. To design effective air pollution mitigation strategies it is essential to quantify the effect of pollutant emission reductions on their concentrations as well as health and ecosystem impacts. Within integrated assessment modeling source-receptor relationships (SRRs) are used that are based on chemistry transport modelling. Currently, these SRRs are made using invariant emission time profiles. The LOTOS-EUROS model equipped with a source attribution module was used to test this assumptions for renewable energy scenarios. Renewable energy availability and thereby fossil fuel back up are strongly dependent on meteorological conditions. We have used the spatially and temporally explicit energy model REMix to derive time profiles for backup power generation. These time profiles were used in LOTOS-EUROS to investigate the effect of emission timing on air pollutant concentrations and SRRs. It is found that the effectiveness of emission reduction in the power sector is significantly lower when accounting for the shift in the way emissions are divided over the year and the correlation of emissions with synoptic situations. The source receptor relationships also changed significantly. This effect was found for both primary and secondary pollutants. Our results indicate that emission timing deserves explicit attention when assessing the impacts of system changes on air quality.

The impact of large cities on air pollution levels usually is determined with models driven by so-called downscaled emission inventories. This implies that annual emissions of air pollutants at the national scale are spatially distributed over a grid using proxy data like population density. These inventories are frequently used for regional air quality modeling but increasingly used also to assess air quality over cities. A key question is how much the assessment of city air pollution and exposure is influenced by downscaling of emission input data.Within this study we compare modeled nitrogen dioxide and particulate matter (PM) concentrations driven by a downscaled emission inventory with modeled concentrations driven by a 'bottom-up' emission inventory for the Paris region. Predicted concentrations and gradients in the concentrations are more consistent with observed concentrations when using the local bottom-up inventory. Both emissions and simulated concentrations of PM over urban sites in Paris are much lower due to different spatial distribution of the anthropogenic emissions. The difference for nearby rural stations is small implicating that the PM urban increment is much smaller than when using the downscaled emission inventory. Urban increments for PM based on conventional down-scaled emissions may therefore be overestimated. (C) 2013 Elsevier Ltd. All rights reserved.

Five air quality models were applied over Portugal for July 2006 with an ensemble purpose. These models were used, with their own meteorology, parameterizations, boundary conditions and chemical mechanisms, but with the same emission data. The validation of the individual models and its ensemble for ozone (O3) and particulate matter was performed using monitoring data from 22 background stations over Portugal. After removing the bias from each model, different ensemble techniques were applied and compared. Besides the median, several weighted ensemble approaches were tested and intercompared: static (SLR) and dynamic (DLR) multiple linear regressions (using less-square optimization method) and the Bayesian Model Averaging (BMA) methodology. The goal of the comparison is to estimate to what extent the ensemble analysis is an improvement with respect to the single model results. The obtained results revealed that no one of the 4 tested ensembles clearly outperforms the others on the basis of statistical parameters and probabilistic analysis (reliability and resolution properties). Nevertheless, statistical results have shown that the application of the weights slightly improves ensemble performance when compared to those obtained from the median ensemble. The same statistical analysis together with the probabilistic measures demonstrates that the SLR and BMA methods are the best performers amongst the assessed methodologies.

An overview of regional-scale quality modeling practices and perspectives in North America and Europe, highlighting the differences and commonalities in how regional-scale air quality modeling systems are being used and evaluated across both continents

Abstract. In this study, the response of secondary inorganic aerosol (SIA) concentrations to changes in precursor emissions during high PM10 episodes over Central Europe in spring 2009 was investigated with the Eulerian Chemistry Transport Model (CTM) REM-Calgrid (RCG). The model performed well in capturing the temporal variation of PM10 and SIA concentrations and was used to analyse the different origin, development and characteristics of the selected high PM10 episodes. SIA concentrations, which attribute to about 50% of the PM10 concentration in north-western Europe, have been studied by means of several emission scenarios varying SO2, NOx and NH3 emissions within a domain covering Germany and within a domain covering Europe. It was confirmed that the response of sulphate, nitrate and ammonium concentrations and deposition fluxes of S and N to SO2, NOx and NH3 emission changes is non-linear. The deviation from linearity was found to be lower for total deposition fluxes of S and N than for SIA concentrations. Furthermore, the study has shown that incorporating explicit cloud chemistry in the model adds non-linear responses to the system and significantly modifies the response of modelled SIA concentrations and S and N deposition fluxes to changes in precursor emissions. The analysis of emission reduction scenarios demonstrates that next to European wide emission reductions additional national NH3 measures in Germany are more effective in reducing SIA concentrations and deposition fluxes than additional national measures on SO2 and NOx.

In this study, the response of secondary inorganic aerosol (SIA) concentrations to changes in precursor emissions during high PM10 episodes over central Europe in spring 2009 was investigated with the Eulerian Chemistry Transport Model (CTM) REM-Calgrid (RCG). The model performed well in capturing the temporal variation of PM10 and SIA concentrations and was used to analyse the different origin, development and characteristics of the selected high PM10 episodes. SIA concentrations, which contribute to about 50% of the PM10 concentration in northwestern Europe, have been studied by means of several model runs for different emission scenarios. SO2, NOx and NH3 emissions have been varied within a domain covering Germany and within a domain covering Europe. It was confirmed that the response of sulfate, nitrate and ammonium concentrations and deposition fluxes of S and N to SO2, NOx and NH3 emission changes is non-linear. The deviation from linearity was found to be lower for total deposition fluxes of S and N than for SIA concentrations. Furthermore, the study has shown that incorporating explicit cloud chemistry in the model adds non-linear responses to the system. It significantly modifies the response of modelled SIA concentrations and S and N deposition fluxes to changes in precursor emissions. The analysis of emission reduction scenario runs demonstrates that next to European-wide emission reductions additional national NH3 measures in Germany are more effective in reducing SIA concentrations and deposition fluxes than additional national measures on SO2 and NOx.

Pollution levels in urban areas and their surrounding rural regions differ due to different sources and density of emissions, different composition of pollutants as well as specific meteorological effects. These concentration differences for PM10 are investigated and compared in this study for three different northwest European urban agglomerations: The German Ruhr area, the Dutch Randstad and the German city of Berlin. Measurement data for PM10 for the years 2003-2008 at urban and rural background stations are selected from the AirBase database to specify the PM10 concentration difference between these urban areas and their surrounding rural regions, here defined as the urban increment. Whereas the absolute and relative measured urban increment averaged over the years 2003-2008 for the Ruhr area (7.4 mu g m(-3), 35%) and Berlin (8.5 mu g m(-3), 46%) are comparable in magnitude, a significantly smaller value is found for the Randstad (3.1 mu g m(-3), 12%). To analyze whether the regional chemistry transport model LOTOS-EUROS is able to reproduce the measured urban increment simulation runs were performed for 2003-2008 on a 0.5 degrees x 0.25 degrees lon-lat grid covering Europe and for the year 2008 on a finer grid of 0.125 degrees x 0.0625 degrees covering the Netherlands and Germany, both with ECMWF meteorology as input. Although the model underestimates the absolute PM10 urban increment averaged over the years 2003-2008 for the Ruhr area (3.3 mu g m(-3), 33%), the Randstad (1.5 mu g m(-3), 12%) and Berlin (1.7 mu g m(-3), 27%), the relative urban increment for the Ruhr area and the Randstad is in general agreement with the measurements. The tested increase of the horizontal resolution gives no systematic improvement of the simulated urban increment. However, an even higher resolution than used here seems to be more appropriate to capture the urban increment (especially for Berlin).The variability of the PM10 urban increment with weather is tested by means of the summer 2003, such an extreme synoptic situation is expected to occur more often in future. Measured and simulated PM10 concentrations in summer 2003 were compared to the summer average of 2003-2008. The response of the observed urban increment was found to depend on the urban area. In general the model reproduces the main features for the Randstad and Berlin.In order to investigate the impact of a changing climate on the PM10 urban increment, simulations were performed with the off-line coupled model system RACMO2 (regional climate model) - LOTOS-EUROS (air quality model) over Europe. Different sets of simulations were carried out using RACMO2 meteorology with ECHAM5 A1B and with MIROC3.2-hires A1B boundary conditions for the time period 1970-2060, as well as with ERA-interim boundary conditions for the time period 1989-2009. Anthropogenic emissions were kept constant in the LOTOS-EUROS simulations. Simulated concentrations differ between the runs using ECHAM and MIROC boundary conditions and both runs differ from the present-day simulations with ERA-interim forcing. The impact of climate change on the modeled PM10 concentrations and the urban increment was found to be small in both scenario runs. However the concentration differences between the simulations forced by either ECHAM or MIROC indicate that PM10 concentration levels are sensitive to circulation patterns rather than temperature change alone, and that PM10 concentration levels may thus change when circulation patterns change in the future. (C) 2013 Elsevier Ltd. All rights reserved.