Christian Seigneur

Effect of bromine chemistry on the atmospheric mercury cycle

[1]xa0Bromine chemistry is believed to play a major role in the atmospheric oxidation of elemental mercury (Hg0) to divalent mercury (HgII). However, its effect on the speciation of atmospheric mercury (Hg) has been mostly ignored in models of the fate and transport of mercury. We investigate the effect of bromine chemistry on Hg speciation for various reaction kinetics and environmental conditions with a box model. Bromine chemistry was also added to the chemical mechanism of a global chemical transport model, and simulations of the global mercury cycle were conducted with different sets of bromine reaction kinetics. The global model simulations conducted with bromine chemistry lead to Hg0 concentrations that are consistent with observations only if the pressure dependence of the kinetics of the oxidation of Hg0 by Br is taken into account. Bromine chemistry is found to reduce the overall lifetime of Hg by about 10%.

Road traffic impact on urban water quality: a step towards integrated traffic, air and stormwater modelling

Methods for simulating air pollution due to road traffic and the associated effects on stormwater runoff quality in an urban environment are examined with particular emphasis on the integration of the various simulation models into a consistent modelling chain. To that end, the models for traffic, pollutant emissions, atmospheric dispersion and deposition, and stormwater contamination are reviewed. The present study focuses on the implementation of a modelling chain for an actual urban case study, which is the contamination of water runoff by cadmium (Cd), lead (Pb), and zinc (Zn) in the Grigny urban catchment near Paris, France. First, traffic emissions are calculated with traffic inputs using the COPERT4 methodology. Next, the atmospheric dispersion of pollutants is simulated with the Polyphemus line source model and pollutant deposition fluxes in different subcatchment areas are calculated. Finally, the SWMM water quantity and quality model is used to estimate the concentrations of pollutants in stormwater runoff. The simulation results are compared to mass flow rates and concentrations of Cd, Pb and Zn measured at the catchment outlet. The contribution of local traffic to stormwater contamination is estimated to be significant for Pb and, to a lesser extent, for Zn and Cd; however, Pb is most likely overestimated due to outdated emissions factors. The results demonstrate the importance of treating distributed traffic emissions from major roadways explicitly since the impact of these sources on concentrations in the catchment outlet is underestimated when those traffic emissions are spatially averaged over the catchment area.

The AER/EPRI global chemical transport model for mercury (CTM-HG)

Mercury (Hg) has an atmospheric residence time on the order of 1 year (Schroeder and Munthe, 1998). Therefore, it can be transported over long distances and the development of source-receptor relationships requires modeling tools that are compatible with fate and transport processes at global scales. Furthermore, the assessment of the potential impact of mercury emission sources at regional scales requires knowledge of the upwind concentrations of mercury species because those upwind “background” concentrations are quite influential for modeling the atmospheric fate and transport of mercury at continental and regional scales. Since there is a paucity of data to specify such boundary conditions, particularly aloft, it is more reliable to obtain such boundary conditions from a global simulation, contingent upon satisfactory performance of the global model. To that end, the AER/EPRI global chemical transport model for mercury (CTM-Hg) was developed to simulate the global cycling of atmospheric mercury. We present first a general description of the model, followed by more detailed discussions of the chemical mechanism and emission inventory. Then, results of a performance evaluation with some available data are presented. Finally, we present results for the contribution of four source regions to atmospheric mercury deposition in those regions.

Assessment of source contributions to air pollution in Beirut, Lebanon: a comparison of source-based and tracer-based modeling approaches

A chemical-transport model (CTM), Polyphemus/Polair3D, is used to investigate the contributions of various anthropogenic and biogenic sources to total organic carbon (OC) in PM2.5 in Beirut, Lebanon, during the summer of 2011. Those results are compared to a tracer-based source apportionment of OC at an ambient site in Beirut where a measurement campaign was conducted in July 2011. The results obtained from the CTM in the base simulation S1 suggest contributions to total simulated OC mass (3.24xa0μg/m3) of 66xa0% (2.14u2009±u20091.07xa0μg/m3) from fossil fuel burning (FFB) and 8xa0% (0.27u2009±u20090.135xa0μg/m3) from biogenic secondary organic carbon (BSOC). The tracer-based approach leads to contribution estimates to total measured OC mass (5.6xa0μg/m3) of 16xa0% (0.9xa0μg/m3u2009±u20090.22) from FFB, 53xa0% (2.9u2009±u20091.7xa0μg/m3) from BSOC, and 32xa0% (1.8u2009±u20090.88xa0μg/m3) from cooking activities. In a second CTM simulation S2, emissions related to cooking activities were added to the emission inventory, monoterpene and sesquiterpene secondary organic aerosol (SOA) surrogate species were added to the boundary conditions, and a lower ratio of semi-volatile organic compounds to primary organic aerosols (SVOC/POA) was used. The S2 results obtained showed contributions to total simulated OC mass (3.01xa0μg/m3) of 33xa0% (0.98u2009±u20090.49xa0μg/m3) from FFB, 18xa0% (0.53u2009±u20090.27xa0μg/m3) from BSOC, and 39xa0% (1.2u2009±u20090.6xa0μg/m3) from cooking activities. The differences between these two methods are discussed in terms of their uncertainties and biases. The comparison of both approaches showed that the model underestimates the secondary fraction of OC, which may be due to underestimations of some biogenic volatile organic compound (VOC) emissions and/or boundary concentrations as well as the use of SOA yields that may not be representative of the eastern Mediterranean region. Concerning the tracer-based approach, the use of tracer/OC ratios that are not specific to Lebanon because of a lack of data could represent a limitation of this methodology. Nevertheless, this comparative analysis suggests that on-road transportation and diesel generators used for electricity production are major sources of atmospheric PM and should be targeted for emission reduction. Finally, cooking activities, which were identified as a significant source of PM with the tracer-based approach, should be studied further.

Sensitivity Analysis of Ambient Particulate Matter to Industrial Emissions Using a Plume-in-Grid Approach: Application in the Greater Paris Region

The Polyphemus Plume-in-Grid (PinG) model, which is based on a 3D Eulerian model and an imbedded puff model, was developed to represent the dispersion and transformation of air pollutants in industrial plumes. It was later improved to take into account particulate matter (PM) formation and transport in order to evaluate secondary PM formation in refinery plumes. The performance of the PinG model, applied to a refinery in the Greater Paris region, was previously evaluated at the regional scale for July 2009, showing satisfactory results for O3 and PM. The PinG model is applied here to the same refinery for a different period, April 2013, when local measurements were available. The refinery is located close to a large NH3 source, which is also treated here using the puff model in order to evaluate the interactions of the plumes of these two industrial sites. Modeled PM is compared here to local measurements in terms of mass concentrations and chemical composition. The measurement sites are located around the refinery and are impacted by the plumes of the two industrial sites. The results show good agreement between measured and modeled PM chemical composition. The sensitivity of the local concentrations to the refinery emissions is evaluated. It is mostly due to primary and secondary inorganic aerosols, emitted and formed in the plumes, and to secondary organic aerosols (SOA) formed from the refinery VOC fugitive emissions.