Publications

2018

• A multi-model comparison of meteorological drivers of surface ozone over Europe
  
  • Otero Noelia
  • Sillmann Jana
  • Mar Kathleen
  • Rust Henning W.
  • Solberg Sverre
  • Andersson Camilla
  • Engardt Magnuz
  • Bergstrom Robert
  • Bessagnet Bertrand
  • Colette Augustin
  • Couvidat Florian
  • Cuvelier Cornelius
  • Tsyro Svetlana
  • Fagerli Hilde
  • Schaap Martijn
  • Manders Astrid
  • Mircea Mihaela
  • Briganti Gino
  • Cappelletti Andrea
  • Adani Mario
  • d'Isidoro Massimo
  • Pay Maria-Teresa
  • Theobald Mark
  • Vivanco Marta G.
  • Wind Peter
  • Ojha Narendra
  • Raffort Valentin
  • Butler Tim
  Atmospheric Chemistry and Physics, European Geosciences Union, 2018, 18, pp.12269-12288. 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. (10.5194/acp-18-12269-2018)
  DOI : 10.5194/acp-18-12269-2018
• High resolution unsteady RANS simulation of wind, thermal effects and pollution dispersion for studying urban renewal scenarios in a neighborhood of Toulouse
  
  • Gao Zhenlan
  • Bresson Raphaël
  • Qu Yongfeng
  • Milliez Maya
  • Munck Cecile De
  • Carissimo Bertrand
  Urban Climate, Elsevier, 2018, 23, pp.114-130. (10.1016/j.uclim.2016.11.002)
  DOI : 10.1016/j.uclim.2016.11.002
• Data assimilation at local scale to improve CFD simulations of atmospheric dispersion: application to 1D shallow-water equations and method comparisons
  
  • Defforge Cécile
  • Carissimo Bertrand
  • Bocquet Marc
  • Armand Patrick
  • Bresson Raphaël
  International Journal of Environment and Pollution, Inderscience, 2018, 64 (1/2/3), pp.90. Atmospheric dispersion modelling requires meteorological inputs over local domains with possibly complex topographies. These local wind fields may be difficult to simulate with CFD models, in particular because of their sensitivity to geometrical features and to model inputs, especially the boundary conditions which are generally provided by larger-scale models or measurements. Using data assimilation, a few measurements inside the domain could add information to the imprecise boundary conditions and thus greatly enhance the precision of the dispersion simulations. Three data assimilation techniques (3DVar, the back and forth nudging algorithm, and the iterative ensemble Kalman smoother) have been adapted to local scale simulations by taking boundary conditions into account instead of initial conditions for which they are usually applied. Their performances have been evaluated at small scales, with a simple representation of the atmosphere into two layers, using 1D solution of the shallow-water equations. (10.1504/IJEP.2018.099151)
  DOI : 10.1504/IJEP.2018.099151
• Intercomparison of three modeling approaches for traffic-related road dust resuspension using two experimental data
  
  • Thouron Laëtitia
  • Seigneur Christian
  • Kim Youngseob
  • Mahe Frédéric
  • Andre Michel
  • Lejri Delphine
  • Villegas Daniel
  • Bruge Benjamin
  • Chanut Hervé
  • Pellan Yann
  Transportation Research Part D: Transport and Environment, Elsevier, 2018, 58, pp.pp.108-121. Two observational campaigns were conducted, one in the Grenoble area (South Eastern France), for the MOCoPo project, near an urban freeway in 2011 and the other one in a Paris suburb, forthe TrafiPollu project, on a major surface street in 2014. PM10 concentrations were measured by Air Rhône-Alpes during the last 10 days of September 2011 for MOCoPo and by Airparif during 3 months from April to June 2014 for TrafiPollu. It has been shown that abrasion and resuspension processes represent a significant part of the total primary PM10 emissions of road traffic. Hereby, resuspended emissions originating from the road are estimated with several approaches and compared to PM10 measurements. We consider two different models available in the literature: HERMES (Pay et al., 2010) and NORTRIP (Denby et al., 2013), which differ in terms of formulation. We also apply an empirical method developed by Thorpe et al. (2007), based on near-road and background pollutant observations. The results vary depending on the traffic conditions and the modeling approach. In all cases, the resuspension emissions simulated are high enough to be considered in air quality modeling (ranging from 9 to 150% of the exhaust emissions). Those resuspension models were combined with atmospheric dispersion models to estimate near-road concentrations. We used a Gaussian line-source model for the Grenoble urban freeway and a street-canyon model (MUNICH) for the Paris suburban boulevard. The contribution of resuspension to traffic-related concentrations is hidden by a strong background contribution, which prevents us from concluding in terms of model performance. Nevertheless, a comparison with another dataset obtained near an urban freeway in Paris suggests that vehicle speed should be taken into account when estimating PM10 resuspension emissions. (10.1016/j.trd.2017.11.003)
  DOI : 10.1016/j.trd.2017.11.003
• Multi-scale modeling of urban air pollution: development and application of a Street-in-Grid model (v1.0) by coupling MUNICH (v1.0) and Polair3D (v1.8.1)
  
  • Kim Youngseob
  • Wu You
  • Seigneur Christian
  • Roustan Yelva
  Geoscientific Model Development Discussions, Copernicus Publ, 2018, 11 (2), pp.611-629. A new multi-scale model of urban air pollution is presented. This model combines a chemistry–transport model (CTM) that includes a comprehensive treatment of atmospheric chemistry and transport on spatial scales down to 1 km and a street-network model that describes the atmospheric concentrations of pollutants in an urban street network. The street-network model is the Model of Urban Network of Intersecting Canyons and Highways (MUNICH), which consists of two main components: a street-canyon component and a street-intersection component. MUNICH is coupled to the Polair3D CTM of the Polyphemus air quality modeling platform to constitute the Street-in-Grid (SinG) model. MUNICH is used to simulate the concentrations of the chemical species in the urban canopy, which is located in the lowest layer of Polair3D, and the simulation of pollutant concentrations above rooftops is performed with Po-lair3D. Interactions between MUNICH and Polair3D occur at roof level and depend on a vertical mass transfer coefficient that is a function of atmospheric turbulence. SinG is used to simulate the concentrations of nitrogen oxides (NO x) and ozone (O 3) in a Paris suburb. Simulated concentrations are compared to NO x concentrations measured at two monitoring stations within a street canyon. SinG shows better performance than MUNICH for nitrogen dioxide (NO 2) concentrations. However, both SinG and MUNICH underestimate NO x. For the case study considered, the model performance for NO x concentrations is not sensitive to using a complex chemistry model in MUNICH and the Leighton NO–NO 2 – O 3 set of reactions is sufficient. (10.5194/gmd-11-611-2018)
  DOI : 10.5194/gmd-11-611-2018