Tropospheric trace gas and aerosol pollutants have adverse effects on health, environment and climate. In order to quantify and mitigate such effects, a wide range of processes leading to the ...formation and transport of pollutants must be considered, understood and represented in numerical models. Regional scale pollution episodes result from the combination of several factors: high emissions (from anthropogenic or natural sources), stagnant meteorological conditions, kinetics and efficiency of the chemistry and the deposition. All these processes are highly variable in time and space, and their relative contribution to the pollutants budgets can be quantified with chemistry-transport models. The CHIMERE chemistry-transport model is dedicated to regional atmospheric pollution event studies. Since it has now reached a certain level a maturity, the new stable version, CHIMERE 2013, is described to provide a reference model paper. The successive developments of the model are reviewed on the basis of published investigations that are referenced in order to discuss the scientific choices and to provide an overview of the main results.
Air pollution causes adverse effects on human health as well as ecosystems and crop yield and also has an impact on climate change trough short-lived climate forcers. To design mitigation strategies ...for air pollution, 3D Chemistry Transport Models (CTMs) have been developed to support the decision process. Increases in model resolution may provide more accurate and detailed information, but will cubically increase computational costs and pose additional challenges concerning high resolution input data. The motivation for the present study was therefore to explore the impact of using finer horizontal grid resolution for policy support applications of the European Monitoring and Evaluation Programme (EMEP) model within the Long Range Transboundary Air Pollution (LRTAP) convention. The goal was to determine the “optimum resolution” at which additional computational efforts do not provide increased model performance using presently available input data. Five regional CTMs performed four runs for 2009 over Europe at different horizontal resolutions.
The models’ responses to an increase in resolution are broadly consistent for all models. The largest response was found for NO2 followed by PM10 and O3. Model resolution does not impact model performance for rural background conditions. However, increasing model resolution improves the model performance at stations in and near large conglomerations. The statistical evaluation showed that the increased resolution better reproduces the spatial gradients in pollution regimes, but does not help to improve significantly the model performance for reproducing observed temporal variability. This study clearly shows that increasing model resolution is advantageous, and that leaving a resolution of 50 km in favour of a resolution between 10 and 20 km is practical and worthwhile. As about 70% of the model response to grid resolution is determined by the difference in the spatial emission distribution, improved emission allocation procedures at high spatial and temporal resolution are a crucial factor for further model resolution improvements.
•Four European CTMs were used to compare model performance at different resolutions.•CTM resolution increase from ∼50 to ∼14 km is worthwhile and practical.•Model performance improves with resolution for NO2 and PM10.•For further resolution increase, high resolution emission and meteorological data are crucial.
NO2 concentrations at the street level are a major concern for urban air quality in Europe and have been regulated under the EU Thematic Strategy on Air Pollution. Despite the legal requirements, ...limit values are exceeded at many monitoring stations with little or no improvement in recent years. In order to assess the effects of future emission control regulations on roadside NO2 concentrations, a downscaling module has been implemented in the GAINS integrated assessment model. The module follows a hybrid approach based on atmospheric dispersion calculations and observations from the AirBase European air quality database that are used to estimate site-specific parameters. Pollutant concentrations at every monitoring site with sufficient data coverage are disaggregated into contributions from regional background, urban increment, and local roadside increment. The future evolution of each contribution is assessed with a model of the appropriate scale: 28 × 28 km grid based on the EMEP Model for the regional background, 7 × 7 km urban increment based on the CHIMERE Chemistry Transport Model, and a chemical box model for the roadside increment. Thus, different emission scenarios and control options for long-range transport as well as regional and local emissions can be analysed. Observed concentrations and historical trends are well captured, in particular the differing NO2 and total NOx = NO + NO2 trends. Altogether, more than 1950 air quality monitoring stations in the EU are covered by the model, including more than 400 traffic stations and 70% of the critical stations. Together with its well-established bottom-up emission and dispersion calculation scheme, GAINS is thus able to bridge the scales from European-wide policies to impacts in street canyons. As an application of the model, we assess the evolution of attainment of NO2 limit values under current legislation until 2030. Strong improvements are expected with the introduction of the Euro 6 emission standard for light duty vehicles; however, for some major European cities, further measures may be required, in particular if aiming to achieve compliance at an earlier time.
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.
Twenty-five biogenic and anthropogenic secondary organic aerosol (SOA) markers have been measured over a one-year period in both gaseous and PM10 phases in the Paris region (France). Seasonal and ...chemical patterns were similar to those previously observed in Europe, but significantly different from the ones observed in America and Asia due to dissimilarities in source precursor emissions. Nitroaromatic compounds showed higher concentrations in winter due to larger emissions of their precursors originating from biomass combustion used for residential heating purposes. Among the biogenic markers, only isoprene SOA marker concentrations increased in summer while pinene SOA markers did not display any clear seasonal trend. The measured SOA markers, usually considered as semi-volatiles, were mainly associated to the particulate phase, except for the nitrophenols and nitroguaiacols, and their gas/particle partitioning (GPP) showed a low temperature and OM concentrations dependency. An evaluation of their GPP with thermodynamic model predictions suggested that apart from equilibrium partitioning between organic phase and air, the GPP of the markers is affected by processes suppressing volatility from a mixed organic and inorganic phase, such as enhanced dissolution in aerosol aqueous phase and non-equilibrium conditions. SOA marker concentrations were used to apportion secondary organic carbon (SOC) sources applying both, an improved version of the SOA-tracer method and positive matrix factorization (PMF) Total SOC estimations agreed very well between both models, except in summer and during a highly processed Springtime PM pollution event in which systematic underestimation by the SOA tracer method was evidenced. As a first approach, the SOA-tracer method could provide a reliable estimation of the average SOC concentrations, but it is limited due to the lack of markers for aged SOA together with missing SOA/SOC conversion fractions for several sources.
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•One-year monitoring of 25 key SOA markers in the Paris region•Seasonal/chemical differences with non-EU data due to source precursor contrasts•SOA marker GPP measurements/modelling highlighting volatility suppressing processes•Good agreement on annual scale between SOA-tracer and PMF SOA source apportionments•Underestimation by the SOA tracer for aged SOA due to missing conversion factors
In this work, an off‐line coupling between the chemistry‐transport model CHIMERE (associated with an aerosol optical module) and the meteorological model Weather Research and Forecasting (WRF) is ...used to study (1) the direct radiative forcing of pollution aerosols during the heat wave of summer 2003 over western Europe and (2) the possible feedbacks of this direct radiative forcing on the surface‐atmosphere system. Simulations performed for the period 7–15 August 2003 reveal a significant decrease of daily mean solar radiation reaching the surface (ΔFBOA = −(10–30) W/m2) because of back scattering at the top of the atmosphere (ΔFTOA = −(1–12) W/m2) and also absorption of solar radiation by polluted particles (ΔFatm = + (5–23) W/m2). During daytime, the aerosol surface dimming induces a mean reduction of both sensible (16 W/m2) and latent (21 W/m2) heat fluxes emitted by the terrestrial surface, resulting in a radiative cooling of the air near the surface (up to 2.9 K/d at noon). Simultaneously, the absorption of solar energy by aerosols causes an atmospheric radiative heating within the planetary boundary layer reaching 1.20 K/d at noon. As a consequence, the direct radiative effect of aerosols is shown to reduce both the planetary boundary layer height (up to 30%) and the horizontal wind speed (up to 6%); that may have contributed to favor the particulate pollution during the heat wave of summer 2003.
Key Points
Direct radiative forcing of pollution aerosols
Possible feedbacks on the surface‐atmosphere system
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 mu m) limit values at individual air quality monitoring stations reporting to the Air-Base database. The modelling approach relies on a combination of bottom up modelling of emissions, simplified atmospheric chemistry and dispersion calculations, and a traffic increment calculation wherever applicable. At each monitoring station fulfilling a few data coverage criteria, measured concentrations in the base year 2009 are explained to the extent possible and then modelled for the past and future. More than 1850 monitoring stations are covered, including more than 300 traffic stations and 80% of the stations which exceeded the EU air quality limit values in 2009. As a validation, we compare modelled trends in the period 2000-2008 to observations, which are well reproduced. The modelling scheme is applied here to quantify explicitly source contributions to ambient concentrations at several critical monitoring stations, displaying the differences in spatial origin and chemical composition of urban roadside PM10 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 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.
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.
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