Influence of boundary conditions and anthropogenic emission inventories on simulated O3 and PM2.5 concentrations over Lebanon

AbstractThis study investigates the influence of boundary conditions and anthropogenic emission inventories on the simulated O3 and PM2.5 concentrations over a middle-eastern country – Lebanon. The Polyphemus chemical transport model (CTM) is used over Lebanon to simulate O3 and PM2.5 concentrations. Comparisons to measurements at a sub-urban site of Beirut between 2 and 13 July 2011 show that O3 is largely over-estimated when concentrations from a large-scale model are used as boundary conditions, as used in Waked et al. (2013). A global anthropogenic emission inventory (EDGAR-HTAP) is used with Polyphemus, in order to provide anthropogenic emissions for the Middle-East domain. Over Lebanon, sensitivity to emissions and to boundary conditions have been investigated. The comparison of EDGAR-HTAP to Waked et al. (2012) over Lebanon highlights high discrepancies between the inventories both in terms of emission estimates and spatial distribution. However, when studying the sensitivity to boundary conditions, O3 is well modeled when a Middle-East domain and the Lebanon domain are nested and thus achieves better statistics. The observed concentration is 48.8 μg m−3 and the respective concentrations for the simulation using MOZART4 and the one using the Polyphemus/Middle-East are 154.8 and 65.1 μg m−3. As for PM2.5 which is less sensitive to regional transport than O3, the influence of the boundary conditions on the PM2.5 concentrations at the site of comparison is low. The observed concentration is 20.7 μg m−3, while the modeled concentrations are 20.7 and 20.1 μg m−3 respectively

Comparison of lidar-derived PM10 with regional modeling and ground-based observations in the frame of MEGAPOLI experiment

International audienceAn innovative approach using mobile lidar measurements was implemented to test the performances of chemistry-transport models in simulating mass concentrations (PM10) predicted by chemistry-transport models. A ground-based mobile lidar (GBML) was deployed around Paris onboard a van during the MEGAPOLI (Megacities: Emissions, urban, regional and Global Atmospheric POLlution and climate effects, and Integrated tools for assessment and mitigation) summer experiment in July 2009. The measurements performed with this Rayleigh-Mie lidar are converted into PM10 profiles using optical-to-mass relationships previously established from in situ measurements performed around Paris for urban and peri-urban aerosols. The method is described here and applied to the 10 measurements days (MD). MD of 1, 15, 16 and 26 July 2009, corresponding to different levels of pollution and atmospheric conditions, are analyzed here in more details. Lidar-derived PM10 are compared with results of simulations from POLYPHEMUS and CHIMERE chemistry-transport models (CTM) and with ground-based observations from the AIRPARIF network. GBML-derived and AIRPARIF in situ measurements have been found to be in good agreement with a mean Root Mean Square Error RMSE (and a Mean Absolute Percentage Error MAPE) of 7.2 μg m−3 (26.0%) and 8.8 μg m−3 (25.2%) with relationships assuming peri-urban and urban-type particles, respectively. The comparisons between CTMs and lidar at ~200 m height have shown that CTMs tend to underestimate wet PM10 concentrations as revealed by the mean wet PM10 observed during the 10 MD of 22.4, 20.0 and 17.5 μg m−3 for lidar with peri-urban relationship, and POLYPHEMUS and CHIMERE models, respectively. This leads to a RMSE (and a MAPE) of 6.4 μg m−3 (29.6%) and 6.4 μg m−3 (27.6%) when considering POLYPHEMUS and CHIMERE CTMs, respectively. Wet integrated PM10 computed (between the ground and 1 km above the ground level) from lidar, POLYPHEMUS and CHIMERE results have been compared and have shown similar results with a RMSE (and MAPE) of 6.3 mg m−2 (30.1%) and 5.2 mg m−2 (22.3%) with POLYPHEMUS and CHIMERE when comparing with lidar-derived PM10 with periurban relationship. The values are of the same order of magnitude than other comparisons realized in previous studies. The discrepancies observed between models and measured PM10 can be explained by difficulties to accurately model the background conditions, the positions and strengths of the plume, the vertical turbulent diffusion (as well as the limited vertical model resolutions) and chemical processes as the formation of secondary aerosols. The major advantage of using vertically resolved lidar observations in addition to surface concentrations is to overcome the problem of limited spatial representativity of surface measurements. Even for the case of a well-mixed boundary layer, vertical mixing is not complete, especially in the surface layer and near source regions. Also a bad estimation of the mixing layer height would introduce errors in simulated surface concentrations, which can be detected using lidar measurements. In addition, horizontal spatial representativity is larger for altitude integrated measurements than for surface measurements, because horizontal inhomogeneities occurring near surface sources are dampened

Dominant aerosol processes during high-pollution episodes over Greater Tokyo

This paper studies two high-pollution episodes over Greater Tokyo: 9 and 10 December 1999, and 31 July and 1 August 2001. Results obtained with the chemistry-transport model (CTM) Polair3D are compared to measurements of inorganic PM2.5. To understand to which extent the aerosol processes modeled in Polair3D impact simulated inorganic PM2.5, Polair3D is run with different options in the aerosol module, e.g. with/without heterogeneous reactions. To quantify the impact of processes outside the aerosol module, simulations are also done with another CTM (CMAQ). In the winter episode, sulfate is mostly impacted by condensation, coagulation, long-range transport, and deposition to a lesser extent. In the summer episode, the effect of long-range transport largely dominates. The impact of condensation/evaporation is dominant for ammonium, nitrate and chloride in both episodes. However, the impact of the thermodynamic equilibrium assumption is limited. The impact of heterogeneous reactions is large for nitrate and ammonium, and taking heterogeneous reactions into account appears to be crucial in predicting the peaks of nitrate and ammonium. The impact of deposition is the same for all inorganic PM2.5. It is small compared to the impact of other processes although it is not negligible. The impact of nucleation is negligible in the summer episode, and small in the winter episode. The impact of coagulation is larger in the winter episode than in the summer episode, because the number of small particles is higher in the winter episode as a consequence of nucleation.Comment: Journal of Geophysical Research D: Atmospheres (15/05/2007) in pres

GENerator of reduced Organic Aerosol mechanism (GENOA v1.0): an automatic generation tool of semi-explicit mechanisms

This paper describes the GENerator of reduced Organic Aerosol mechanism (GENOA) that produces semi-explicit mechanisms for simulating the formation and evolution of secondary organic aerosol (SOA) in air quality models. Using a series of predefined reduction strategies and evaluation criteria, GENOA trains and reduces SOA mechanisms from near-explicit chemical mechanisms (e.g., the Master Chemical Mechanism – MCM) under representative atmospheric conditions. As a consequence, these trained SOA mechanisms can preserve the accuracy of detailed gas-phase chemical mechanisms on SOA formation (e.g., molecular structures of crucial organic compounds, the effect of “non-ideality”, and the hydrophilic/hydrophobic partitioning of aerosols), with a size (in terms of reaction and species numbers) that is manageable for three-dimensional (3-D) aerosol modeling (e.g., regional chemical transport models). Applied to the degradation of sesquiterpenes (as β-caryophyllene) from MCM, GENOA builds a concise SOA mechanism (2 % of the MCM size) that consists of 23 reactions and 15 species, with 6 of them being condensable. The generated SOA mechanism has been evaluated regarding its ability to reproduce SOA concentrations under the varying atmospheric conditions encountered over Europe, with an average error lower than 3 %.</p

TWIST1 expression is associated with high-risk neuroblastoma and promotes primary and metastatic tumor growth.

The embryonic transcription factors TWIST1/2 are frequently overexpressed in cancer, acting as multifunctional oncogenes. Here we investigate their role in neuroblastoma (NB), a heterogeneous childhood malignancy ranging from spontaneous regression to dismal outcomes despite multimodal therapy. We first reveal the association of TWIST1 expression with poor survival and metastasis in primary NB, while TWIST2 correlates with good prognosis. Secondly, suppression of TWIST1 by CRISPR/Cas9 results in a reduction of tumor growth and metastasis colonization in immunocompromised mice. Moreover, TWIST1 knockout tumors display a less aggressive cellular morphology and a reduced disruption of the extracellular matrix (ECM) reticulin network. Additionally, we identify a TWIST1-mediated transcriptional program associated with dismal outcome in NB and involved in the control of pathways mainly linked to the signaling, migration, adhesion, the organization of the ECM, and the tumor cells versus tumor stroma crosstalk. Taken together, our findings confirm TWIST1 as promising therapeutic target in NB

Technical Note: The air quality modeling system Polyphemus

International audiencePolyphemus is an air quality modeling platform which aims at covering the scope and the abilities of modern air quality systems. It deals with applications from local scale to continental scale, using two Gaussian models and two Eulerian models. It manages passive tracers, radioactive decay, photochemistry and aerosol dynamics. The structure of the system includes four independent levels with data management, physical parameterizations, numerical solvers and high-level methods such as data assimilation. This enables sensitivity and uncertainty analysis, primarily through multimodel approaches. On top of the models, drivers implement advanced methods such as model coupling or data assimilation

Impact of wildfires on particulate matter in the Euro-Mediterranean in 2007: sensitivity to some parameterizations of emissions in air quality models

This study examines the uncertainties on air quality modeling associated with the integration of wildfire emissions in chemistry-transport models (CTMs). To do so, aerosol concentrations during the summer of 2007, which was marked by severe fire episodes in the Euro-Mediterranean region especially in the Balkans (20–31 July, 24–30 August 2007) and Greece (24–30 August 2007), are analyzed. Through comparisons to observations from surface networks and satellite remote sensing, we evaluate the abilities of two CTMs, Polyphemus/Polair3D and CHIMERE, to simulate the impact of fires on the regional particulate matter (PM) concentrations and optical properties. During the two main fire events, fire emissions may contribute up to 90&thinsp;% of surface PM2.5 concentrations in the fire regions (Balkans and Greece), with a significant regional impact associated with long-range transport. Good general performances of the models and a clear improvement of PM2.5 and aerosol optical depth (AOD) are shown when fires are taken into account in the models with high correlation coefficients. Two sources of uncertainties are specifically analyzed in terms of surface PM2.5 concentrations and AOD using sensitivity simulations: secondary organic aerosol (SOA) formation from intermediate and semi-volatile organic compounds (I/S-VOCs) and emissions' injection heights. The analysis highlights that surface PM2.5 concentrations are highly sensitive to injection heights (with a sensitivity that can be as high as 50&thinsp;% compared to the sensitivity to I/S-VOC emissions which is lower than 30&thinsp;%). However, AOD which is vertically integrated is less sensitive to the injection heights (mostly below 20&thinsp;%) but highly sensitive to I/S-VOC emissions (with sensitivity that can be as high as 40&thinsp;%). The maximum statistical dispersion, which quantifies uncertainties related to fire emission modeling, is up to 75&thinsp;% for PM2.5 in the Balkans and Greece, and varies between 36&thinsp;% and 45&thinsp;% for AOD above fire regions. The simulated number of daily exceedance of World Health Organization (WHO) recommendations for PM2.5 over the considered region reaches 30 days in regions affected by fires and ∼10 days in fire plumes, which is slightly underestimated compared to available observations. The maximum statistical dispersion (σ) on this indicator is also large (with σ reaching 15 days), showing the need for better understanding of the transport and evolution of fire plumes in addition to fire emissions.</p

Precursors and formation of secondary organic aerosols from wildfires in the Euro-Mediterranean region

This work aims at quantifying the relative contribution of secondary organic aerosol (SOA) precursors emitted by wildfires to organic aerosol (OA) formation during summer of 2007 over the Euro-Mediterranean region, where intense wildfires occurred. A new SOA formation mechanism, H2Oaro, including recently identified aromatic volatile organic compounds (VOCs) emitted from wildfires, is developed based on smog chamber experiment measurements under low- and high-NOx regimes. The aromatic VOCs included in the mechanism are toluene, xylene, benzene, phenol, cresol, catechol, furan, naphthalene, methylnaphthalene, syringol, guaiacol, and structurally assigned and unassigned compounds with at least six carbon atoms per molecule (USC&gt;6). This mechanism H2Oaro is an extension of the H2O (hydrophilic–hydrophobic organic) aerosol mechanism: the oxidation of the precursor forms surrogate species with specific thermodynamic properties (volatility, oxidation degree and affinity to water). The SOA concentrations over the Euro-Mediterranean region in summer of 2007 are simulated using the chemistry transport model (CTM) Polair3D of the air-quality platform Polyphemus, where the mechanism H2Oaro was implemented. To estimate the relative contribution of the aromatic VOCs, intermediate volatility, semi-volatile and low-volatility organic compounds (I/S/L-VOCs), to wildfires OA concentrations, different estimations of the gaseous I/S/L-VOC emissions (from primary organic aerosol – POA – using a factor of 1.5 or from non-methanic organic gas – NMOG – using a factor of 0.36) and their ageing (one-step oxidation vs. multi-generational oxidation) are also tested in the CTM. Most of the particle OA concentrations are formed from I/S/L-VOCs. On average during the summer of 2007 and over the Euro-Mediterranean domain, they are about 10 times higher than the OA concentrations formed from VOCs. However, locally, the OA concentrations formed from VOCs can represent up to 30&thinsp;% of the OA concentrations from biomass burning. Amongst the VOCs, the main contributors to SOA formation are phenol, benzene and catechol (CAT; 47&thinsp;%); USC&gt;6 compounds (23&thinsp;%); and toluene and xylene (12&thinsp;%). Sensitivity studies of the influence of the VOCs and the I/S/L-VOC emissions and chemical ageing mechanisms on PM2.5 concentrations show that surface PM2.5 concentrations are more sensitive to the parameterization used for gaseous I/S/L-VOC emissions than for ageing. Estimating the gaseous I/S/L-VOC emissions from POA or from NMOG has a high impact on local surface PM2.5 concentrations (reaching −30&thinsp;% in the Balkans, −8&thinsp;% to −16&thinsp;% in the fire plume and +8&thinsp;% to +16&thinsp;% in Greece). Considering the VOC as SOA precursors results in a moderate increase in PM2.5 concentrations mainly in the Balkans (up to 24&thinsp;%) and in the fire plume (+10&thinsp;%).</p

Modelling concentration heterogeneities in streets using the street-network model MUNICH

Populations in urban areas are exposed to high local concentrations of pollutants, such as nitrogen dioxide and particulate matter, because of unfavourable dispersion conditions and the proximity to traffic. To simulate these concentrations over cities, models like the street-network model MUNICH (Model of Urban Network of Intersecting Canyons and Highways) rely on parameterizations to represent the air flow and the concentrations of pollutants in streets. In the current version, MUNICH v2.0, concentrations are assumed to be homogeneous in each street segment. A new version of MUNICH, where the street volume is discretized, is developed to represent the street gradients and to better estimate peoples' exposure. Three vertical levels are defined in each street segment. A horizontal discretization is also introduced under specific conditions by considering two zones with a parameterization taken from the Operational Street Pollution Model (OSPM). Simulations are performed over two districts of Copenhagen, Denmark, and one district of greater Paris, France. Results show an improvement in the comparison to observations, with higher concentrations at the bottom of the street, closer to traffic, of pollutants emitted by traffic (NOx, black carbon, organic matter). These increases reach up to 60 % for NO2 and 30 % for PM10 in comparison to MUNICH v2.0. The aspect ratio (ratio between building height and street width) influences the extent of the increase of the first-level concentrations compared to the average of the street. The increase is higher for wide streets (low aspect ratio and often higher traffic) by up to 53 % for NOx and 18 % for PM10. Finally, a sensitivity analysis with regard to the influence of the street network highlights the importance of using the model MUNICH with a network rather than with a single street.</p