Showing papers by "Karine Sartelet published in 2013"

Evaluation of the Weather Research and Forecast/Urban Model Over Greater Paris

Abstract: Meteorological modelling in the planetary boundary layer (PBL) over Greater Paris is performed using the Weather Research and Forecast (WRF) numerical model. The simulated meteorological fields are evaluated by comparison with mean diurnal observational data or mean vertical profiles of temperature, wind speed, humidity and boundary-layer height from 6 to 27 May 2005. Different PBL schemes, which parametrize the atmospheric turbulence in the PBL using different turbulence closure schemes, may be used in the WRF model. The sensitivity of the results to four PBL schemes (two non-local closure schemes and two local closure schemes) is estimated. Uncertainties in the PBL schemes are compared to the influence of the urban canopy model (UCM) and the updated Coordination of Information on the Environment (CORINE) land-use data. Using the UCM and the CORINE land-use data produces more realistic modelled meteorological fields. The wind speed, which is overestimated in the simulations without the UCM, is improved below 1,000 m height. Furthermore, the modelled PBL heights during nighttime are strongly modified, with an increase that may be as high as 200 %. At night, the impact of changing the PBL scheme is lower than the impact of using the UCM and the CORINE land-use data.

Modeling secondary organic aerosol in an urban area: application to Paris, France

Abstract: . A secondary organic aerosol (SOA) model, H2O (Hydrophilic/Hydrophobic Organic), is evaluated over the Paris area. This model treats the formation of SOA with two kinds of surrogate species: hydrophilic species (which condense preferentially on an aqueous phase) and hydrophobic species (which condense only on an organic phase). These surrogates species are formed from the oxidation in the atmosphere of volatile organic compounds (VOC) by radicals (HO and NO3) and ozone. These VOC are either biogenic (isoprene, monoterpenes and sesquiterpenes) or anthropogenic (mainly aromatic compounds). This model includes the formation of aerosols from different precursors (biogenic precursors, aromatics), and semi-volatile organic compounds (SVOC) from traffic. The H2O aerosol model was incorporated into the Polyphemus air quality modeling platform and applied to the Paris area and evaluated by comparison to measurements performed during the Megapoli campaign in July 2009. The comparison to measurements in the suburbs and in the city center of Paris shows that the model gives satisfactory results for both elemental carbon (EC) and organic carbon (OC). However, the model gives a peak of OC concentrations in the morning due to high emissions from traffic, which does not appear in measurements. Uncertainties in the modeled temperature, which can affect the gas-particle partitioning, in the partitioning of primary SVOC or underestimation of primary organic aerosol (POA) evaporation by the model could explain the differences between model and measurements. Moreover, using a theoretical mechanism for the oxidation of primary SVOC and intermediate volatility organic compounds (IVOC), POA concentrations were found to be likely overestimated by models due to the use of simple partitioning constants (which do not take into account the affinity of a compound with the liquid aerosol solution) or due to the assumption that the organic aerosol solution is a one-phase ideal solution. The organic aerosol in the city center of Paris was found to be originating mostly from distant sources with only 30 to 38% due to local sources.

Evaluating the capability of regional-scale air quality models to capture the vertical distribution of pollutants

Abstract: . This study is conducted in the framework of the Air Quality Modelling Evaluation International Initiative (AQMEII) and aims at the operational evaluation of an ensemble of 12 regional-scale chemical transport models used to predict air quality over the North American (NA) and European (EU) continents for 2006. The modelled concentrations of ozone and CO, along with the meteorological fields of wind speed (WS) and direction (WD), temperature (T), and relative humidity (RH), are compared against high-quality in-flight measurements collected by instrumented commercial aircraft as part of the Measurements of OZone, water vapour, carbon monoxide and nitrogen oxides by Airbus In-service airCraft (MOZAIC) programme. The evaluation is carried out for five model domains positioned around four major airports in NA (Portland, Philadelphia, Atlanta, and Dallas) and one in Europe (Frankfurt), from the surface to 8.5 km. We compare mean vertical profiles of modelled and measured variables for all airports to compute error and variability statistics, perform analysis of altitudinal error correlation, and examine the seasonal error distribution for ozone, including an estimation of the bias introduced by the lateral boundary conditions (BCs). The results indicate that model performance is highly dependent on the variable, location, season, and height (e.g. surface, planetary boundary layer (PBL) or free troposphere) being analysed. While model performance for T is satisfactory at all sites (correlation coefficient in excess of 0.90 and fractional bias ≤ 0.01 K), WS is not replicated as well within the PBL (exhibiting a positive bias in the first 100 m and also underestimating observed variability), while above 1000 m, the model performance improves (correlation coefficient often above 0.9). The WD at NA airports is found to be biased in the PBL, primarily due to an overestimation of westerly winds. RH is modelled well within the PBL, but in the free troposphere large discrepancies among models are observed, especially in EU. CO mixing ratios show the largest range of modelled-to-observed standard deviations of all the examined species at all heights and for all airports. Correlation coefficients for CO are typically below 0.6 for all sites and heights, and large errors are present at all heights, particularly in the first 250 m. Model performance for ozone in the PBL is generally good, with both bias and error within 20%. Profiles of ozone mixing ratios depend strongly on surface processes, revealed by the sharp gradient in the first 2 km (10 to 20 ppb km−1). Modelled ozone in winter is biased low at all locations in the NA, primarily due to an underestimation of ozone from the BCs. Most of the model error in the PBL is due to surface processes (emissions, transport, photochemistry), while errors originating aloft appear to have relatively limited impact on model performance at the surface. Suggestions for future work include interpretation of the model-to-model variability and common sources of model bias, and linking CO and ozone bias to the bias in the meteorological fields. Based on the results from this study, we suggest possible in-depth, process-oriented and diagnostic investigations to be carried out next.

Application of WRF/Chem-MADRID and WRF/Polyphemus in Europe – Part 2: Evaluation of chemical concentrations and sensitivity simulations

Abstract: . An offline-coupled model (WRF/Polyphemus) and an online-coupled model (WRF/Chem-MADRID) are applied to simulate air quality in July 2001 at horizontal grid resolutions of 0.5° and 0.125° over Western Europe. The model performance is evaluated against available surface and satellite observations. The two models simulate different concentrations in terms of domainwide performance statistics, spatial distribution, temporal variations, and column abundance. WRF/Chem-MADRID at 0.5° gives higher values than WRF/Polyphemus for the domainwide mean and over polluted regions in Central and southern Europe for all surface concentrations and column variables except for the tropospheric ozone residual (TOR). Compared with observations, WRF/Polyphemus gives better statistical performance for daily HNO3, SO2, and NO2 at the European Monitoring and Evaluation Programme (EMEP) sites, maximum 1 h O3 at the AirBase sites, PM2.5 at the AirBase sites, maximum 8 h O3 and PM10 composition at all sites, column abundance of CO, NO2, TOR, and aerosol optical depth (AOD), whereas WRF/Chem-MADRID gives better statistical performance for NH3, hourly SO2, NO2, and O3 at the AirBase and BDQA (Base de donnees de la qualite de l'air) sites, maximum 1 h O3 at the BDQA and EMEP sites, and PM10 at all sites. WRF/Chem-MADRID generally reproduces well the observed high hourly concentrations of SO2 and NO2 at most sites except for extremely high episodes at a few sites, and WRF/Polyphemus performs well for hourly SO2 concentrations at most rural or background sites where pollutant levels are relatively low, but it underpredicts the observed hourly NO2 concentrations at most sites. Both models generally capture well the daytime maximum 8 h O3 concentrations and diurnal variations of O3 with more accurate peak daytime and minimal nighttime values by WRF/Chem-MADRID, but neither model reproduces extremely low nighttime O3 concentrations at several urban and suburban sites due to underpredictions of NOx and thus insufficient titration of O3 at night. WRF/Polyphemus gives more accurate concentrations of PM2.5, and WRF/Chem-MADRID reproduces better the observations of PM10 concentrations at all sites. The differences between model predictions and observations are mostly caused by inaccurate representations of emissions of gaseous precursors and primary PM species, as well as biases in the meteorological predictions. The differences in model predictions are caused by differences in the heights of the first model layers and thickness of each layer that affect vertical distributions of emissions, model treatments such as dry/wet deposition, heterogeneous chemistry, and aerosol and cloud, as well as model inputs such as emissions of soil dust and sea salt and chemical boundary conditions of CO and O3 used in both models. WRF/Chem-MADRID shows a higher sensitivity to grid resolution than WRF/Polyphemus at all sites. For both models, the use of a finer grid resolution generally leads to an overall better statistical performance for most variables, with greater spatial details and an overall better agreement in temporal variations and magnitudes at most sites. The use of online biogenic volatile organic compound (BVOC) emissions gives better statistical performance for hourly and maximum 8 h O3 and PM2.5 and generally better agreement with their observed temporal variations at most sites. Because it is an online model, WRF/Chem-MADRID offers the advantage of accounting for various feedbacks between meteorology and chemical species. However, this model comparison suggests that atmospheric pollutant concentrations are most sensitive in state-of-the-science air quality models to vertical structure, inputs, and parameterizations for dry/wet removal of gases and particles in the model.

Application of WRF/Chem-MADRID and WRF/Polyphemus in Europe – Part 1: Model description, evaluation of meteorological predictions, and aerosol–meteorology interactions

Abstract: . Comprehensive model evaluation and comparison of two 3-D air quality modeling systems (i.e., the Weather Research and Forecast model (WRF)/Polyphemus and WRF with chemistry and the Model of Aerosol Dynamics, Reaction, Ionization, and Dissolution (MADRID) (WRF/Chem-MADRID)) are conducted over Western Europe. Part 1 describes the background information for the model comparison and simulation design, the application of WRF for January and July 2001 over triple-nested domains in Western Europe at three horizontal grid resolutions: 0.5°, 0.125°, and 0.025°, and the effect of aerosol/meteorology interactions on meteorological predictions. Nine simulated meteorological variables (i.e., downward shortwave and longwave radiation fluxes (SWDOWN and LWDOWN), outgoing longwave radiation flux (OLR), temperature at 2 m (T2), specific humidity at 2 m (Q2), relative humidity at 2 m (RH2), wind speed at 10 m (WS10), wind direction at 10 m (WD10), and precipitation (Precip)) are evaluated using available observations in terms of spatial distribution, domainwide daily and site-specific hourly variations, and domainwide performance statistics. The vertical profiles of temperature, dew points, and wind speed/direction are also evaluated using sounding data. WRF demonstrates its capability in capturing diurnal/seasonal variations and spatial gradients and vertical profiles of major meteorological variables. While the domainwide performance of LWDOWN, OLR, T2, Q2, and RH2 at all three grid resolutions is satisfactory overall, large positive or negative biases occur in SWDOWN, WS10, and Precip even at 0.125° or 0.025° in both months and in WD10 in January. In addition, discrepancies between simulations and observations exist in T2, Q2, WS10, and Precip at mountain/high altitude sites and large urban center sites in both months, in particular, during snow events or thunderstorms. These results indicate the model's difficulty in capturing meteorological variables in complex terrain and subgrid-scale meteorological phenomena, due to inaccuracies in model initialization parameterization (e.g., lack of soil temperature and moisture nudging), limitations in the physical parameterizations (e.g., shortwave radiation, cloud microphysics, cumulus parameterizations, and ice nucleation treatments) as well as limitations in surface heat and moisture budget parameterizations (e.g., snow-related processes, subgrid-scale surface roughness elements, and urban canopy/heat island treatments and CO2 domes). While the use of finer grid resolutions of 0.125° and 0.025° shows some improvements for WS10, WD10, Precip, and some mesoscale events (e.g., strong forced convection and heavy precipitation), it does not significantly improve the overall statistical performance for all meteorological variables except for Precip. The WRF/Chem simulations with and without aerosols show that aerosols lead to reduced net shortwave radiation fluxes, 2 m temperature, 10 m wind speed, planetary boundary layer (PBL) height, and precipitation and increase aerosol optical depth, cloud condensation nuclei, cloud optical depth, and cloud droplet number concentrations over most of the domain. These results indicate a need to further improve the model representations of the above parameterizations as well as aerosol–meteorology interactions at all scales.

Assimilation of ground versus lidar observations for PM 10 forecasting

Abstract: . This article investigates the potential impact of future ground-based lidar networks on analysis and short-term forecasts of particulate matter with a diameter smaller than 10 μm (PM10). To do so, an Observing System Simulation Experiment (OSSE) is built for PM10 data assimilation (DA) using optimal interpolation (OI) over Europe for one month from 15 July to 15 August 2001. First, using a lidar network with 12 stations and representing the "true" atmosphere by a simulation called "nature run", we estimate the efficiency of assimilating the lidar network measurements in improving PM10 concentration for analysis and forecast. It is compared to the efficiency of assimilating concentration measurements from the AirBase ground network, which includes about 500 stations in western Europe. It is found that assimilating the lidar observations decreases by about 54% the root mean square error (RMSE) of PM10 concentrations after 12 h of assimilation and during the first forecast day, against 59% for the assimilation of AirBase measurements. However, the assimilation of lidar observations leads to similar scores as AirBase's during the second forecast day. The RMSE of the second forecast day is improved on average over the summer month by 57% by the lidar DA, against 56% by the AirBase DA. Moreover, the spatial and temporal influence of the assimilation of lidar observations is larger and longer. The results show a potentially powerful impact of the future lidar networks. Secondly, since a lidar is a costly instrument, a sensitivity study on the number and location of required lidars is performed to help define an optimal lidar network for PM10 forecasts. With 12 lidar stations, an efficient network in improving PM10 forecast over Europe is obtained by regularly spacing the lidars. Data assimilation with a lidar network of 26 or 76 stations is compared to DA with the previously-used lidar network. During the first forecast day, the assimilation of 76 lidar stations' measurements leads to a better score (the RMSE decreased by about 65%) than AirBase's (the RMSE decreased by about 59%).

Modeling air pollution in Lebanon: evaluation at a suburban site in Beirut during summer

Abstract: . Beirut, the capital of Lebanon, which is located on the eastern shore of the Mediterranean basin, experiences high air pollution episodes. Annual average concentrations of coarse and fine particulate matter (PM2.5) as well as nitrogen oxides (NOx) often exceed the World Health Organization (WHO) guidelines. Therefore, improving air quality in this region is essential. The Polyphemus/Polair3D modeling system is used here to investigate air pollution episodes in Beirut during 2 to 18 July 2011. The modeling domain covers two nested grids of 1 and 5 km horizontal resolution over greater Beirut and Lebanon, respectively. The anthropogenic emission inventory was developed earlier (Waked et al., 2012). The Weather and Research Forecasting (WRF) model is used to generate the meteorological fields and the Model of Emissions of Gases and Aerosols from Nature (MEGAN) is used for biogenic emissions. The results of the study are compared to measurements from a field campaign conducted in the suburb of Beirut during 2–18 July 2011. The model reproduces satisfactorily the concentrations of most gaseous pollutants, the total mass of PM2.5 as well as PM2.5 elemental carbon (EC), organic carbon (OC), and sulfate. Ozone concentrations are overestimated and it appears that this overestimation results mainly from the boundary conditions.

Investigating the Impact of Aqueous-Phase Chemistry and Wet Deposition on Organic Aerosol Formation Using a Molecular Surrogate Modeling Approach

Abstract: A molecular surrogate representation of secondary organic aerosol (SOA) formation is used to investigate the effect of aqueous-phase (in clouds and particles) chemical processing and wet deposition on SOA atmospheric concentrations. To that end, the hydrophilic/hydrophobic organic (H(2)O) model was augmented to account for several gas/aqueous-phase equilibria and aqueous-phase processes, including the formation of oxalic, glyoxilic and pyruvic acids, the oxidation of methyl vinyl ketone (MVK) and methacrolein (MACR), the formation of tetrols and organosulfates from epoxydiols (IEPOX), and further oxidation of water-soluble SOA (aging). Among those processes, SOA chemical aging and IEPOX reactions led to the most significant increases (up to 1 μg m(-3) in some areas) in SOA concentrations in a one-month summer simulation over Europe. However, large uncertainties remain in the gas/aqueous-phase partitioning of oxalic acid, MVK, and MACR. Below-cloud scavenging of SOA precursor gases and of gas-phase SVOC was found to affect SOA concentrations by up to 20%, which suggests that it should be taken into account in air quality models.

Four-dimensional evaluation of regional air quality models

Abstract: Introduction Conclusions References