Atmospheric composition forecasting in Europe

The atmospheric composition is a societal issue and, following new European directives, its forecast is now recommended to quantify the air quality. It concerns both gaseous and particles species, identified as potential problems for health. In Europe, numerical systems providing daily air quality forecasts are numerous and, mostly, operated by universities. Following recent European research projects (GEMS, PROMOTE), an organization of the air quality forecast is currently under development. But for the moment, many platforms exist, each of them with strengths and weaknesses. This overview paper presents all existing systems in Europe and try to identify the main remaining gaps in the air quality forecast knowledge. As modeling systems are now able to reasonably forecast gaseous species, and in a lesser extent aerosols, the future directions would concern the use of these systems with ensemble approaches and satellite data assimilation. If numerous improvements were recently done on emissions and chemistry knowledge, improvements are still needed especially concerning meteorology, which remains a weak point of forecast systems. Future directions will also concern the use of these forecast tools to better understand and quantify the air pollution impact on health

Aerosol chemical and optical properties over the Paris area within ESQUIF project

Aerosol chemical and optical properties are extensively investigated for the first time over the Paris Basin in July 2000 within the ESQUIF project. The measurement campaign offers an exceptional framework to evaluate the performances of the chemistry-transport model CHIMERE in simulating concentrations of gaseous and aerosol pollutants, as well as the aerosol-size distribution and composition in polluted urban environments against ground-based and airborne measurements. A detailed comparison of measured and simulated variables during the second half of July with particular focus on 19 and 31 pollution episodes reveals an overall good agreement for gas-species and aerosol components both at the ground level and along flight trajectories, and the absence of systematic biases in simulated meteorological variables such as wind speed, relative humidity and boundary layer height as computed by the MM5 model. A good consistency in ozone and NO concentrations demonstrates the ability of the model to reproduce the plume structure and location fairly well both on 19 and 31 July, despite an underestimation of the amplitude of ozone concentrations on 31 July. The spatial and vertical aerosol distributions are also examined by comparing simulated and observed lidar vertical profiles along flight trajectories on 31 July and confirm the model capacity to simulate the plume characteristics. The comparison of observed and modeled aerosol components in the southwest suburb of Paris during the second half of July indicates that the aerosol composition is rather correctly reproduced, although the total aerosol mass is underestimated by about 20%. The simulated Parisian aerosol is dominated by primary particulate matter that accounts for anthropogenic and biogenic primary particles (40%), and inorganic aerosol fraction (40%) including nitrate (8%), sulfate (22%) and ammonium (10%). The secondary organic aerosols (SOA) represent 12% of the total aerosol mass, while the mineral dust accounts for 8%. The comparison demonstrates the absence of systematic errors in the simulated sulfate, ammonium and nitrates total concentrations. However, for nitrates the observed partition between fine and coarse mode is not reproduced. In CHIMERE there is a clear lack of coarse-mode nitrates. This calls for additional parameterizations in order to account for the heterogeneous formation of nitrate onto dust particles. Larger discrepancies are obtained for the secondary organic aerosols due to both inconsistencies in the SOA formation processes in the model leading to an underestimation of their mass and large uncertainties in the determination of the measured aerosol organic fraction. The observed mass distribution of aerosols is not well reproduced, although no clear explanation can be given

Direct radiative effect of the Russian wildfires and its impact on air temperature and atmospheric dynamics during August 2010

International audienceIn this study, we investigate the shortwave aerosol direct radiative forcing (ADRF) and its feedback on air temperature and atmospheric dynamics during a major fire event that occurred in Russia during August 2010. The methodology is based on an offline coupling between the CHIMERE chemistry-transport and the Weather Research and Forecasting (WRF) models. First, simulations for the period 5–12 August 2010 have been evaluated by using AERONET (AErosol RObotic NETwork) and satellite measurements of the POLarization and Directionality of the Earth's Reflectance (POLDER) and the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) sensors. During this period, elevated POLDER aerosol optical thickness (AOT) is found over a large part of eastern Europe, with values above 2 (at 550 nm) in the aerosol plume. According to CALIOP observations, particles remain confined to the first five kilometres of the atmospheric layer. Comparisons with satellite measurements show the ability of CHIMERE to reproduce the regional and vertical distribution of aerosols during their transport from the source region. Over Moscow, AERONET measurements indicate an important increase of AOT (340 nm) from 0.7 on 5 August to 2–4 between 6 and 10 August when the aerosol plume was advected over the city. Particles are mainly observed in the fine size mode (radius in the range 0.2–0.4 μm) and are characterized by elevated single-scattering albedo (SSA) (0.95–0.96 between 440 and 1020 nm). Comparisons of simulations with AERONET measurements show that aerosol physical–optical properties (size distribution, AOT, SSA) have been well simulated over Moscow in terms of intensity and/or spectral dependence. Secondly, modelled aerosol optical properties have been used as input in the radiative transfer code of WRF to evaluate their direct radiative impact. Simulations indicate a significant reduction of solar radiation at the ground (up to 80–150 W m−2 in diurnal averages over a large part of eastern Europe due to the presence of the aerosol plume. This ADRF causes an important reduction of the near-surface air temperature between 0.2 and 2.6° on a regional scale. Moscow has been affected by the aerosol plume, especially between 6 and 10 August. During this period, aerosol causes a significant reduction of surface shortwave radiation (up to 70–84 W m−2 in diurnal averages) with a moderate part (20–30%) due to solar absorption within the aerosol layer. The resulting feedbacks lead to a cooling of the air up to 1.6° at the surface and 0.1° at an altitude of 1500–2000 m (in diurnal averages), that contribute to stabilize the atmospheric boundary layer (ABL). Indeed, a reduction of the ABL height of 13 to 65% has been simulated during daytime in presence of aerosols. This decrease is the result of a lower air entrainment as the vertical wind speed in the ABL is shown to be reduced by 5 to 80% (at midday) when the feedback of the ADRF is taken into account. However, the ADRF is shown to have a lower impact on the horizontal wind speed, suggesting that the dilution of particles would be mainly affected by the weakening of the ABL development and associated vertical entrainment. Indeed, CHIMERE simulations driven by the WRF meteorological fields including this ADRF feedback result in a large increase in the modelled near-surface PM10 concentrations (up to 99%). This is due to their lower vertical dilution in the ABL, which tend to reduce model biases with the ground PM10 values observed over Moscow during this specific period

The Impact of MM5 and WRF Meteorology over Complex Terrain on CHIMERE Model Calculations

The objective of this study is to evaluate the impact of meteorological input data on calculated gas and aerosol concentrations. We use two different meteorological models (MM5 and WRF) together with the chemistry transport model CHIMERE.We focus on the Po valley area (Italy) for January and June 2005. Firstly we evaluate the meteorological parameters with observations. The analysis shows that the performance of both models in calculating surface parameters is similar, however differences are still observed. Secondly, we analyze the impact of using MM5 and WRF on calculated PM10 and O3 concentrations. In general CHIMERE/MM5 and CHIMERE/WRF underestimate the PM10 concentrations for January. The difference in PM10 concentrations for January between CHIMERE/MM5 and CHIMERE/WRF is around a factor 1.6 (PM10 higher for CHIMERE/MM5). This difference and the larger underestimation in PM10 concentrations by CHIMERE/WRF are related to the differences in heat fluxes and the resulting PBL heights calculated by WRF. In general the PBL height by WRF meteorology is a factor 2.8 higher at noon in January than calculated by MM5. This study showed that the difference in microphysics scheme has an impact on the profile of cloud liquid water (CLW) calculated by the meteorological driver and therefore on the production of SO4 aerosol. A sensitivity analysis shows that changing the Noah Land Surface Model (LSM) in our WRF pre-processing for the 5-layer soil temperature model, calculated monthly mean Correspondence to: A. de Meij ([email protected]) PM10 concentrations increase by 30%, due to the change in the heat fluxes and the resulting PBL heights. For June, PM10 calculated concentrations by CHIMERE/MM5 and CHIMERE/WRF are similar and agree with the observations. Calculated O3 values for June are in general overestimated by a factor 1.3 by CHIMERE/MM5 and CHIMERE/WRF. High temporal correlations are found between modeled and observed O3 concentrations.JRC.H.4 - Transport and air qualit

Modelling street level PM10 concentrations across Europe: source apportionment and possible futures

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 um) limit values at individual air quality monitoring stations reporting to the AirBase 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

EURODELTA - Evaluation of a Sectoral Approach to Integrated Assessment Modeling - Second Report

The EURODELTA project is a continuing collaboration between the European Commission Joint Research Centre (JRC) at Ispra (Italy) and five air quality modeling teams at Ineris (France), the Free University of Berlin (Germany), Met.no (Norway), TNO (Netherlands) and SMHI (Sweden). This phase of Eurodelta investigates how different air quality models would represent the effect on pollutant impacts of applying, on a European scale, emission reductions to individual emission sectors. The reason for doing this is to test whether there are important sensitivities not captured by the sound science approach to air quality policy making on a European scale which is based on an integrated assessment (IA) approach and embodied in the IIASA RAINS/GAINS model. This study shows that there are important differences between sectors in the amount of concentration (deposition) reduction obtained by changing a pollutant emission. This difference is not accounted for in the present process used to evaluate future national emissions ceiling reductions for both beneficial effect and cost-effectiveness. This raises the possibility that, when national bodies consider how to implement an emission ceiling taking account of the information used in deriving that ceiling, choices might be made that are less effective than expected.JRC.DDG.H.4-Transport and air qualit

European atmosphere in 2050, a regional air quality and climate perspective under CMIP5 scenarios

To quantify changes in air pollution in Europe at the 2050 horizon, we designed a comprehensive modelling system that captures the external factors considered to be most relevant and relies on up-to-date and consistent sets of air pollution and climate policy scenarios. Global and regional climate as well as global chemistry simulations are based on the recent Representative Concentrations Pathways (RCP) produced for the Fifth Assessment Report (AR5) of IPCC whereas regional air quality modelling is based on the updated emissions scenarios produced in the framework of the Global Energy Assessment. We explored two diverse scenarios: a reference scenario where climate policies are absent and a mitigation scenario which limits global temperature rise to within 2 degrees C by the end of this century. This first assessment of projected air quality and climate at the regional scale based on CMIP5 (5th Climate Model Intercomparison Project) climate simulations is in line with the existing literature using CMIP3. The discrepancy between air quality simulations obtained with a climate model or with meteorological reanalyses is pointed out. Sensitivity simulations show that the main factor driving future air quality projections is air pollutant emissions, rather than climate change or long range transport. Whereas the well documented "climate penalty" bearing upon ozone over Europe is confirmed, other features appear less robust compared to the literature: such as the impact of climate on PM2.5. The quantitative disentangling of each contributing factor shows that the magnitude of the ozone climate penalty has been overstated in the past while on the contrary the contribution of the global ozone burden is overlooked in the literature

Modeling organic aerosols during MILAGRO: importance of biogenic secondary organic aerosols

The meso-scale chemistry-transport model CHIMERE is used to assess our understanding of major sources and formation processes leading to a fairly large amount of organic aerosols – OA, including primary OA (POA) and secondary OA (SOA) – observed in Mexico City during the MILAGRO field project (March 2006). Chemical analyses of submicron aerosols from aerosol mass spectrometers (AMS) indicate that organic particles found in the Mexico City basin contain a large fraction of oxygenated organic species (OOA) which have strong correspondence with SOA, and that their production actively continues downwind of the city. The SOA formation is modeled here by the one-step oxidation of anthropogenic (i.e. aromatics, alkanes), biogenic (i.e. monoterpenes and isoprene), and biomass-burning SOA precursors and their partitioning into both organic and aqueous phases. Conservative assumptions are made for uncertain parameters to maximize the amount of SOA produced by the model. The near-surface model evaluation shows that predicted OA correlates reasonably well with measurements during the campaign, however it remains a factor of 2 lower than the measured total OA. Fairly good agreement is found between predicted and observed POA within the city suggesting that anthropogenic and biomass burning emissions are reasonably captured. Consistent with previous studies in Mexico City, large discrepancies are encountered for SOA, with a factor of 2–10 model underestimate. When only anthropogenic SOA precursors were considered, the model was able to reproduce within a factor of two the sharp increase in OOA concentrations during the late morning at both urban and near-urban locations but the discrepancy increases rapidly later in the day, consistent with previous results, and is especially obvious when the column-integrated SOA mass is considered instead of the surface concentration. The increase in the missing SOA mass in the afternoon coincides with the sharp drop in POA suggesting a tendency of the model to excessively evaporate the freshly formed SOA. Predicted SOA concentrations in our base case were extremely low when photochemistry was not active, especially overnight, as the SOA formed in the previous day was mostly quickly advected away from the basin. These nighttime discrepancies were not significantly reduced when greatly enhanced partitioning to the aerosol phase was assumed. Model sensitivity results suggest that observed nighttime OOA concentrations are strongly influenced by a regional background SOA (~1.5 μg/m&lt;sup&gt;3&lt;/sup&gt;) of biogenic origin which is transported from the coastal mountain ranges into the Mexico City basin. The presence of biogenic SOA in Mexico City was confirmed by SOA tracer-derived estimates that have reported 1.14 (&amp;plusmn;0.22) μg/m&lt;sup&gt;3&lt;/sup&gt; of biogenic SOA at T0, and 1.35 (&amp;plusmn;0.24) μg/m&lt;sup&gt;3&lt;/sup&gt; at T1, which are of the same order as the model. Consistent with other recent studies, we find that biogenic SOA does not appear to be underestimated significantly by traditional models, in strong contrast to what is observed for anthropogenic pollution. The relative contribution of biogenic SOA to predicted monthly mean SOA levels (traditional approach) is estimated to be more than 30% within the city and up to 65% at the regional scale which may help explain the significant amount of modern carbon in the aerosols inside the city during low biomass burning periods. The anthropogenic emissions of isoprene and its nighttime oxidation by NO&lt;sub&gt;3&lt;/sub&gt; were also found to enhance the SOA mean concentrations within the city by an additional 15%. Our results confirm the large underestimation of the SOA production by traditional models in polluted regions (estimated as 10–20 tons within the Mexico City metropolitan area during the daily peak), and emphasize for the first time the role of biogenic precursors in this region, indicating that they cannot be neglected in urban modeling studies

Model evaluation and ensemble modelling of surface-level ozone in Europe and North America in the context of AQMEII

More than ten state-of-the-art regional air quality models have been applied as part of the Air Quality Model Evaluation International Initiative (AQMEII). These models were run by twenty independent groups in Europe and North America. Standardised modelling outputs over a full year (2006) from each group have been shared on the web-distributed ENSEMBLE system, which allows for statistical and ensemble analyses to be performed by each group. The estimated ground-level ozone mixing ratios from the models are collectively examined in an ensemble fashion and evaluated against a large set of observations from both continents. The scale of the exercise is unprecedented and offers a unique opportunity to investigate methodologies for generating skilful ensembles of regional air quality models outputs. Despite the remarkable progress of ensemble air quality modelling over the past decade, there are still outstanding questions regarding this technique. Among them, what is the best and most beneficial way to build an ensemble of members? And how should the optimum size of the ensemble be determined in order to capture data variability as well as keeping the error low? These questions are addressed here by looking at optimal ensemble size and quality of the members. The analysis carried out is based on systematic minimization of the model error and is important for performing diagnostic/probabilistic model evaluation. It is shown that the most commonly used multi-model approach, namely the average over all available members, can be outperformed by subsets of members optimally selected in terms of bias, error, and correlation. More importantly, this result does not strictly depend on the skill of the individual members, but may require the inclusion of low-ranking skill-score members. A clustering methodology is applied to discern among members and to build a skilful ensemble based on model association and data clustering, which makes no use of priori knowledge of model skill. Results show that, while the methodology needs further refinement, by optimally selecting the cluster distance and association criteria, this approach can be useful for model applications beyond those strictly related to model evaluation, such as air quality forecasting. (C) 2012 Elsevier Ltd. All rights reserved.Peer reviewe

EURODELTA II - Evaluation of a Sectoral Approach to Integrated Assessment Modelling Including the Mediterranean Sea

The EURODELTA II (ED II) project is a continuing collaboration between the European Commission Joint Research Centre (JRC) at Ispra (Italy) and five air quality modelling teams at Ineris (France), the Free University of Berlin (Germany), Met.no (Norway), TNO (Netherlands) and SMHI (Sweden) in which the results from air quality model simulations are brought together in the JRC assessment toolkit and compared with each other and against data. ED I examined the common performance of the models in predicting recent (2000) and future (2020) air quality in Europe using the concept of a model ensemble to measure robustness of predictions. The spread of predictions about the ensemble gave a measure of uncertainty for each predicted value. In a 2020 world the effect of making emission reductions for key pollutants of NOx, SO2, VOC and NH3 independently in France, Germany and Italy, and of NOx and SOx in sea areas, was investigated. Source-receptor relationships used in integrated assessment (IA) modelling were derived for all the models and compared to assess how model choice might affect this key input. ED II builds on this project by taking a closer look at how the different models represent the effect on pollutant impacts on a European scale of applying emission reductions to individual emission sectors. A total of 60 different emission scenario calculations were run using meteorology from 1999. Sectors were defined using the SNAP97 designation and main focus was on Sectors 1,2,3,4,7 and 10 with some scenarios including sectors 6 and 8. Sector definitions are given in the introduction. Although the time-line for the scenarios is 2020 in line with the EU CAFE study and with the NECD review, an extra set of three 2010 scenarios was run for the Mediterranean Sea. These examine the effect of EU legislation requiring the use of a 0.1% S fuel for ships at berth in ports and the use of a maximum 1.5% S fuel for ferries. The main recommendation is that, at minimum, validation calculations are carried out as part of the NEC process to examine if the implied sectoral reductions are able to deliver the intended benefits. If sectoral weights could be incorporated into the integrated assessment itself then this may lead to an overall better recommendation for emission ceilings.JRC.H.4 - Transport and air qualit