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The Lagrangian chemistry and transport model ATLAS: simulation and validation of stratospheric chemistry and ozone loss in the winter 1999/2000

The Lagrangian chemistry and transport model ATLAS: simulation and validation of stratospheric chemistry and ozone loss in the winter 1999/2000

Abstract. ATLAS is a new global Lagrangian Chemistry and Transport Model (CTM), which includes a stratospheric chemistry scheme with 46 active species, 171 reactions, heterogeneous chemistry on polar stratospheric clouds and a Lagrangian denitrification module. Lagrangian (trajectory- based) models have several important advantages over con- ventional Eulerian models, including the absence of spuri- ous numerical diffusion, efficient code parallelization and no limitation of the largest time step by the Courant-Friedrichs- Lewy criterion. This work describes and validates the stratospheric chemistry scheme of the model. Stratospheric chemistry is simulated with ATLAS for the Arctic win- ter 1999/2000, with a focus on polar ozone depletion and denitrification. The simulations are used to validate the chemistry module in comparison with measurements of the SOLVE/THESEO 2000 campaign. A Lagrangian denitrifica- tion module, which is based on the simulation of the nucle- ation, sedimentation and growth of a large number of polar stratospheric cloud particles, is used to model the substantial denitrification that occured in this winter.
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ECHMERIT V1.0 – a new global fully coupled mercury-chemistry and transport model

ECHMERIT V1.0 – a new global fully coupled mercury-chemistry and transport model

The new global mercury-chemistry and transport model ECHMERIT has undergone an initial performance evalua- tion and a detailed description of all important developed model components was given. These included a precise de- scription of the modules for wet and dry deposition calcu- lation, the implemented emission databases, as well as the chemistry scheme used to simulate tropospheric photochem- istry and mercury chemistry. The ECHMERIT model aims to minimize modelling inconsistencies, that are a common problem in CTMs. As ECHMERIT is run in online coupled mode, meteorology, emissions, deposition and chemistry are calculated contemporaneously and on the same model grid. In that way it is aimed at a reduction of modelling uncertain- ties due to interpolation of meteorological input variables on the CTM model grid and due to the lack of representation of high-frequency meteorology features. ECHMERIT also uses the same convective transport scheme for model physics as for tracer transport. Not doing this can lead to additional in- consistencies, as in common offline coupled models. A study of Grell et al. (2004) for example showed large errors in the vertical mass distribution in a highly resolved regional model when running in offline mode.
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The Lagrangian chemistry and transport model ATLAS: validation of advective transport and mixing

The Lagrangian chemistry and transport model ATLAS: validation of advective transport and mixing

Abstract. We present a new global Chemical Transport Model (CTM) with full stratospheric chemistry and La- grangian transport and mixing called ATLAS (Alfred We- gener InsTitute LAgrangian Chemistry/Transport System). Lagrangian (trajectory-based) models have several important advantages over conventional Eulerian (grid-based) models, including the absence of spurious numerical diffusion, ef- ficient code parallelization and no limitation of the largest time step by the Courant-Friedrichs-Lewy criterion. The ba- sic concept of transport and mixing is similar to the approach in the commonly used CLaMS model. Several aspects of the model are different from CLaMS and are introduced and val- idated here, including a different mixing algorithm for lower resolutions which is less diffusive and agrees better with ob- servations with the same mixing parameters. In addition, val- ues for the vertical and horizontal stratospheric bulk diffusion coefficients are inferred and compared to other studies. This work focusses on the description of the dynamical part of the model and the validation of the mixing algorithm. The chem- istry module, which contains 49 species, 170 reactions and a detailed treatment of heterogeneous chemistry, will be pre- sented in a separate paper.
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The global chemistry transport model TM5: description and evaluation of the tropospheric chemistry version 3.0

The global chemistry transport model TM5: description and evaluation of the tropospheric chemistry version 3.0

face albedo following Krol and van Weele (1997). Although heavily parameterized, this method avoids the radiative trans- fer calculation of the actinic flux for each of the 140 spectral bins included on the wavelength grid, which is expensive in a 3-D global chemistry transport model. For the calculation of the optical depth of clouds we use the cloud liquid water con- tent taken from the ECMWF meteorological data and assume an effective radius of 8 µm for all cloud droplets. For cir- rus particles we use the associated ice water content, where the particle shape is assumed to be hexagonal. A maximum overlap type scaling method is then used to determine the ef- fective optical depth introduced throughout the atmospheric column. Here the optical depth at each model level is scaled with the maximal cloud cover in the column. In total 16 pho- tolysis rates are included in the scheme (see Table 4). 3.3 Heterogeneous and aqueous phase reactions For the loss of gaseous trace species via heterogeneous oxi- dation processes, the model explicitly accounts for the oxida- tion of SO 2 in cloud and aerosol through aqueous phase reac-
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Integration of prognostic aerosol–cloud interactions in a chemistry transport model coupled offline to a regional climate model

Integration of prognostic aerosol–cloud interactions in a chemistry transport model coupled offline to a regional climate model

Abstract. To reduce uncertainties and hence to obtain a bet- ter estimate of aerosol (direct and indirect) radiative forc- ing, next generation climate models aim for a tighter cou- pling between chemistry transport models and regional cli- mate models and a better representation of aerosol–cloud in- teractions. In this study, this coupling is done by first forc- ing the Rossby Center regional climate model (RCA4) with ERA-Interim lateral boundaries and sea surface temperature (SST) using the standard cloud droplet number concentration (CDNC) formulation (hereafter, referred to as the “stand- alone RCA4 version” or “CTRL” simulation). In the stand- alone RCA4 version, CDNCs are constants distinguishing only between land and ocean surface. The meteorology from this simulation is then used to drive the chemistry transport model, Multiple-scale Atmospheric Transport and Chemistry (MATCH), which is coupled online with the aerosol dynam- ics model, Sectional Aerosol module for Large Scale Ap- plications (SALSA). CDNC fields obtained from MATCH– SALSA are then fed back into a new RCA4 simulation. In this new simulation (referred to as “MOD” simulation), all parameters remain the same as in the first run except for the CDNCs provided by MATCH–SALSA. Simulations are car- ried out with this model setup for the period 2005–2012 over Europe, and the differences in cloud microphysical proper- ties and radiative fluxes as a result of local CDNC changes and possible model responses are analysed.
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A quasi chemistry-transport model mode for EMAC

A quasi chemistry-transport model mode for EMAC

Abstract. A quasi chemistry-transport model mode (QCTM) is presented for the numerical chemistry-climate simulation system ECHAM/MESSy Atmospheric Chemistry (EMAC). It allows for a quantification of chemical signals through sup- pression of any feedback between chemistry and dynamics. Noise would otherwise interfere too strongly. The signal is calculated from the difference of two QCTM simulations, a reference simulation and a sensitivity simulation. In order to avoid the feedbacks, the simulations adopt the following of- fline chemical fields: (a) offline mixing ratios of radiatively active substances enter the radiation scheme, (b) offline mix- ing ratios of nitric acid enter the scheme for re-partitioning and sedimentation from polar stratospheric clouds, (c) and offline methane oxidation is the exclusive source of chemi- cal water-vapor tendencies. Any set of offline fields suffices to suppress the feedbacks, though may be inconsistent with the simulation setup. An adequate set of offline climatolo- gies can be produced from a non-QCTM simulation using the setup of the reference simulation. Test simulations reveal the particular importance of adequate offline fields associated with (a). Inconsistencies from (b) are negligible when using adequate fields of nitric acid. Acceptably small inconsisten- cies come from (c), but should vanish for an adequate pre- scription of chemical water vapor tendencies. Toggling be- tween QCTM and non-QCTM is done via namelist switches and does not require a source code re-compilation.
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Sensitivity of chemistry-transport model simulations to the duration of chemical and transport operators: a case study with GEOS-Chem v10-01

Sensitivity of chemistry-transport model simulations to the duration of chemical and transport operators: a case study with GEOS-Chem v10-01

Abstract. Chemistry-transport models involve considerable computational expense. Fine temporal resolution offers ac- curacy at the expense of computation time. Assessment is needed of the sensitivity of simulation accuracy to the dura- tion of chemical and transport operators. We conduct a series of simulations with the GEOS-Chem chemistry-transport model at different temporal and spatial resolutions to ex- amine the sensitivity of simulated atmospheric composition to operator duration. Subsequently, we compare the species simulated with operator durations from 10 to 60 min as typ- ically used by global chemistry-transport models, and iden- tify the operator durations that optimize both computational expense and simulation accuracy. We find that longer contin- uous transport operator duration increases concentrations of emitted species such as nitrogen oxides and carbon monoxide since a more homogeneous distribution reduces loss through chemical reactions and dry deposition. The increased con- centrations of ozone precursors increase ozone production with longer transport operator duration. Longer chemical operator duration decreases sulfate and ammonium but in- creases nitrate due to feedbacks with in-cloud sulfur dioxide oxidation and aerosol thermodynamics. The simulation du- ration decreases by up to a factor of 5 from fine (5 min) to coarse (60 min) operator duration. We assess the change in simulation accuracy with resolution by comparing the root mean square difference in ground-level concentrations of ni- trogen oxides, secondary inorganic aerosols, ozone and car- bon monoxide with a finer temporal or spatial resolution taken as “truth”. Relative simulation error for these species
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Assimilation of surface NO 2and O3 observations into the SILAM chemistry transport model

Assimilation of surface NO 2and O3 observations into the SILAM chemistry transport model

Data assimilation is defined (e.g. Kalnay, 2003) as the numerical process of using model fields and observations to produce a physically and statistically consistent repre- sentation of the atmospheric state – often in order to ini- tialise the subsequent forecast. The main techniques used in atmospheric models include the optimal interpolation (OI, Gandin 1963), variational methods (3D-Var and 4D-Var, Le Dimet and Talagrand, 1986; Lorenc, 1986), and the stochas- tic methods based on the ensemble Kalman filter (EnKF, Evensen, 2003, 1994). Each of the methods has been ap- plied in air quality modelling. Statistical interpolation meth- ods were used by Blond and Vautard (2004) for surface ozone analyses and by Tombette et al. (2009) for particulate matter. The EnKF method has been utilised by several authors (Con- stantinescu et al., 2007; Curier et al., 2012; Gaubert et al., 2014) especially for ozone modelling. The 3D-Var method has been applied in regional air quality models by Jaumouillé et al. (2012) and Schwartz et al. (2012), while the computa- tionally more demanding 4D-Var method has been demon- strated by Elbern and Schmidt (2001) and Chai et al. (2007). Partly due to its significance in relation to health effects, the most commonly assimilated chemical component has been ozone.
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Modeling lightning-NOx chemistry on a sub-grid scale in a global chemical transport model

Modeling lightning-NOx chemistry on a sub-grid scale in a global chemical transport model

effects on a sub-grid scale are represented via a fuel tracer in order to follow the amount of the emitted species in the plume and an effective reaction rate for the ozone production and nitric acid production and destruction during the plume’s dilution in the background (Cariolle et al., 2009; Paoli et al., 2011). The parameterization requires a proper estimation of the characteristic plume lifetime, during which the nonlin- ear interactions between species are important and simulated via specific rates of conversion. The approach ensures the mass conservation of species in the model. This is the only method which considers a plume evolution related to the lo- cal NO x emissions, allowing the transport of the nonlinear
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Modeling lightning-NOx chemistry at sub-grid scale in a global chemical transport model

Modeling lightning-NOx chemistry at sub-grid scale in a global chemical transport model

Bechtold, P., Bazile, E., Guichard, F., Mascart, P., and Richard, E.: A mass-flux convection scheme for regional and global models, Q. J. Roy. Meteor. Soc., 127, 869–886, 2000. 34097 Bey, I., Jacob, D. J., Yantosca, R. M., Logan, J. A., Field, B. D., Fiore, A. M., Li, Q., Liu, H. Y., Mickley, L. J., and Schultz, M. G.: Global modeling of tropospheric chemistry with assimilated meteorology: model description and evaluation, J. Geophys. Res., 106, 23073–23095, 2001.

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Improving the prediction of an atmospheric chemistry transport model using gradient boosted regression trees

Improving the prediction of an atmospheric chemistry transport model using gradient boosted regression trees

during the day similar to those seen in the US). If there is a fundamental mismatch between the model’s description of the site and the reality (ocean vs land), the bias-predictor is unable to completely remove the bias. For the two clean tropical sites (Cape Verde and Cape Point in South Africa) the base model already does a reasonable job (Sherwen et al., 2016) so the bias corrected version improves little and slightly reduces the NMB performance at Cape Verde from 0.03 to 0.04. For the Antarctic site the large bias evident in the model (Sherwen et al., 2016) is almost completely removed by the bias corrector but that 160
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First implementation of secondary inorganic aerosols in the MOCAGE version R2.15.0 chemistry transport model

First implementation of secondary inorganic aerosols in the MOCAGE version R2.15.0 chemistry transport model

on the annual mean at the global scale. This new set of bins will become relevant when microphysical processes such as nucleation are implemented in a future version of the model. On this basis, it was possible to introduce secondary inor- ganic aerosols in MOCAGE. SIA results from a partition be- tween the gaseous phase and the aerosol phase. This partition depends on compound concentrations both in the gaseous and aerosol phases and the ambient conditions: tempera- ture and humidity. This partition can be solved using a ther- modynamic equilibrium model. We choose for this purpose to use the latest version of the thermodynamic equilibrium model called ISORROPIA II (Nenes et al., 1998; Fountoukis and Nenes, 2007), which is used here in the deliquescent configuration. ISORROPIA is commonly used in state-of- the-art CTMs, for instance, in CHIMERE (Bessagnet et al., 2004) and LOTOS-EUROS (Schaap et al., 2008). Sulfate, nitrate and ammonium aerosol concentrations are simulated by ISORROPIA, each of these species being represented in MOCAGE with six concentrations for each of the six size bins. ISORROPIA gives the thermodynamic equilibrium be- tween 12 liquid aerosol species (see Table 2), 9 solid aerosol species (see Table 3) and 3 gaseous compounds (see Table 4). Wexler and Seinfeld (1990) showed that the time constant to achieve the equilibrium ranges from a few seconds for high aerosol mass concentrations and small aerosol sizes to more than a day for low mass concentrations and large particle radii. Nevertheless, we assume in MOCAGE that the equi- librium is reached in the 15 min chemical update frequency for the following reasons. The aim of the model is to be used mainly for air quality, especially the forecast of PM 10 and
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An alternative way to evaluate chemistry-transport model variability

An alternative way to evaluate chemistry-transport model variability

To estimate the quality of CTMs, model output results are usually compared with available observations. These com- parisons have been performed for as long as the models have existed; they are crucial for quantifying the ability of models to reproduce particular events or a general behav- ior. The quantification of the model quality is performed in every research work. It depends on the case being studied, the modeled variables and the spatial and temporal resolu- tions. The comparison between observations and model out- puts is a complex task and has to take into account numer- ous factors such as the spatial representativeness of the mon- itoring stations (Valari and Menut, 2008; Solazzo and Gal- marini, 2015). For many years, the best approach to evaluate a model’s results has been discussed and, in the field of at- mospheric composition, numerous methods were proposed. It is not possible to give an exhaustive list of all validation studies and we present some examples here.
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High-resolution air quality simulation over Europe with the chemistry transport model CHIMERE

High-resolution air quality simulation over Europe with the chemistry transport model CHIMERE

favoured and the associated low dispersive conditions en- hance nitrate during these periods. Hence, the highest mea- sured and modelled concentrations are observed during the winter period. The smallest FB is observed during this season (−68.4 %) and a rather high R value (0.67) is calculated, in- dicating that the temporal variability of nitrate concentrations is well reproduced by CHIMERE during this period. How- ever, it is also shown that the nitrate is largely underestimated throughout the year (FB = − 103.5 %). Several explanations concerning the general underestimation of nitrate can be con- sidered. First, the previously described overestimation of sul- fate in poor ammonia regimes could contribute to the un- derestimation. Second, coarse nitrate chemistry is not repre-
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Global sensitivity and uncertainty analysis of an atmospheric chemistry transport model: the FRAME model (version 9.15.0) as a case study

Global sensitivity and uncertainty analysis of an atmospheric chemistry transport model: the FRAME model (version 9.15.0) as a case study

Previously, local one-at-a-time (OAT) sensitivity analy- sis has been used to investigate ACTM sensitivity because it is less computationally demanding than global sensitivity analysis that requires a large number of simultaneous pertur- bations of all inputs of interest. However, there are signifi- cant disadvantages associated with OAT analysis: the inter- actions between the input parameters and non-linearities in the model response cannot be identified; additionally, as the number of input parameters increases, the fraction of param- eter space investigated tends to 0 (Jimenez and Landgrebe, 1998; Saltelli and Annoni, 2010). Therefore, local OAT sen- sitivity analysis is only applicable when the effects of the different inputs are all independent of each other and model response is linear for the range of investigated inputs. Many previous publications that include ACTM sensitivity analysis use the OAT approach but fail to acknowledge its limitations (Appel et al., 2007; Borge et al., 2008; Capaldo and Pandis, 1997; Labrador et al., 2005; Makar et al., 2009).
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Curriculum vitae of the LOTOS–EUROS (v2.0) chemistry transport model

Curriculum vitae of the LOTOS–EUROS (v2.0) chemistry transport model

and can be found in Manders-Groot et al. (2016a). A kinetic pre-processor is used which makes it relatively straightfor- ward to add or modify chemical reactions. For secondary in- organic chemistry Isorropia II (Fountoukis and Nenes, 2007) is used and for the heterogeneous chemistry on wet aerosol we refer to Wichink Kruit et al. (2012b). A pH-dependent cloud chemistry is also used (Banzhaf et al., 2012). These chemical processes are used by default. Currently secondary organic aerosol is by default not modelled. Given the un- realistically small amounts of SOA added by modules like SORGAM (Schell et al., 2001) that are used by other models the impact of SOA on total modelled particulate matter was too small to enhance model performance. Even more impor- tantly, the uncertainties involved in such approaches may in- troduce errors. We have now included the option to use the 1-D VBS approach (Donahue et al., 2006) with nine volatil- ity classes in a very conservative way. Anthropogenic emis- sions of primary organic material are assigned to the four lowest volatility classes and an additional 1.5 times this mass is assigned to the higher five classes. There is no consen- sus in literature on how emissions should be distributed over the volatility classes. Our choice is based on the idea that emissions of organic material including condensables is 2.5 times the primary organic material reported in the emission inventory (an assumption based on Shrivastava et al., 2008) but with our own constraint that the total of the lower four classes should match the reported primary organic material emissions to be consistent with the default option without VBS. Isoprene and VOC contribute to SOA formation but the impact of terpene is not currently taken into account. Al- though the impact of the latter is significant due to the rela- tively high mass of terpene compared to isoprene, emissions and conversion rates are rather uncertain (Bergström et al., 2012; Zhang et al., 2013). Therefore the VBS is not used by default.
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Diagnosing the stratosphere to troposphere flux of ozone in a chemistry transport model

Diagnosing the stratosphere to troposphere flux of ozone in a chemistry transport model

vectorized form of the second-order moments algorithm and air mass conservation [Prather, 1986; Prather et al., 1987]. Thus, if resolved by the CTM grid (600 m in the vertical), stratospheric folds will be maintained and are not likely to be mixed into the troposphere by numerical diffusion. Stratospheric ozone is simulated with linearized net photo- chemical rates (LINOZ [McLinden et al., 2000]). The ozone simulation with full tropospheric chemistry at T63 resolu- tion has been extensively validated against the satellite, ozonesonde, in situ aircraft and lidar observations during TRACE-P period (late February to early April 2001) [Wild et al., 2003, 2004; Hsu et al., 2004]. Stratospheric intrusions are well captured in the model. This success is attributed mostly to the well-simulated stratospheric ozone in the CTM and the ECMWF meteorology.
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Implementation and evaluation of an array of chemical solvers in the Global Chemical Transport Model GEOS-Chem

Implementation and evaluation of an array of chemical solvers in the Global Chemical Transport Model GEOS-Chem

description file globchem.dat and creates three KPP input files – also containing information on the chemical mecha- nism, but in KPP format. Second, KPP processes these in- put files and generates Fortran90 chemical simulation code; the model files are then copied into the GEOS-Chem v7- 04-10 directory. A special directive has been implemented in KPP to generate code that interfaces with GEOS-Chem. The third step involves running the gckpp parser.pl to mod- ify GEOS-Chem source code to correctly call the KPP gen- erated gas-phase chemistry simulation routines. The process is discussed in detail below.
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The Chemistry CATT-BRAMS model (CCATT-BRAMS 4.5): a regional atmospheric model system for integrated air quality and weather forecasting and research

The Chemistry CATT-BRAMS model (CCATT-BRAMS 4.5): a regional atmospheric model system for integrated air quality and weather forecasting and research

http://retro.enes.org) for 26 species and is complemented by other species provided by the “Emission Database for Global Atmospheric Research – version 4.2” (EDGAR-4.2, http://edgar.jrc.ec.europa, Olivier et al., 1996, 1999). This version includes most direct greenhouse gases, 4 ozone pre- cursor species and 3 acidifying gases, primary aerosol par- ticles and stratospheric ozone depleting species. It also in- cludes urban/industrial information specifically for the South American continent based on local inventories (Alonso et al., 2010). Currently, all urban/industrial emissions are re- leased in the lowest model layer. However, if emissions from point sources (e.g., stacks) are available, information on stack heights can be easily included. For biomass burning, the PREP-CHEM-SRC includes emissions provided by the Global Fire Emissions Database (GFEDv2) based on Giglio et al. (2006) and van der Werf et al. (2006), or emissions can also be estimated directly from satellite remote sensing fire detections using the Brazilian Biomass Burning Emis- sion Model (3BEM, Longo et al., 2010) as included in the tool. In both cases, fire emissions are available for 107 dif- ferent species. The biomass burning emission estimate is di- vided into two contributions, namely smoldering, which re- leases material in the lowest model layer, and flaming, which makes use of an embedded on-line 1-D cloud model in each column of the 3-D transport model to determine the verti- cal injection layer. In this case, the cloud model is integrated using current environmental conditions (temperature, water vapor mixing ratio and horizontal wind) provided by the host model (Freitas et al., 2006, 2007, 2010). Biogenic emissions are also considered via the Global Emissions Inventory Ac- tivity of the Atmospheric Composition Change: the Euro- pean Network (GEIA/ACCENT, http://www.aero.jussieu.fr/ projet/ACCENT/description.php) for 12 species and derived by the Model of Emissions of Gases and Aerosols from Na- ture (MEGAN, Guenther et al., 2006) for 15 species. Other emissions include volcanic ashes (Mastin et al., 2009), vol- canic degassing (Diehl, 2009; Diehl et al., 2012), biofuel use and agricultural waste burning inventories developed by Yevich and Logan (2003).
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Modeling anthropogenically controlled secondary organic aerosols in a megacity: a simplified framework for global and climate models

Modeling anthropogenically controlled secondary organic aerosols in a megacity: a simplified framework for global and climate models

As CO is an important model component for this study, it is important to evaluate whether the model can reproduce the measured CO levels. Hodzic et al. (2009) have shown that CO inside Mexico City is generally well captured by the model in comparison to the RAMA monitoring stations, suggesting that the Mexico City emissions are reasonable with the regard to CO, which is consistent with several previ- ous evaluations of the CO emissions inventory (Zavala et al., 2006; Molina et al., 2007, 2010). However, comparison with aircraft measurements (Hodzic et al., 2010a) suggested the model tendency to underpredict regional CO levels. This un- derprediction may be due to too low emissions in urban areas outside Mexico City, which are taken from the Mexico NEI inventory. CO boundary conditions from the monthly clima- tology of the LMDZ/INCA global chemistry-transport model could also be too low and contribute somewhat to this gap. However as the population in Mexico City is 20 million, but in other urban areas in Central Mexico is about 10 million, or about 1/2 of the population in Mexico City (Molina et al., 2010), the regional emissions of CO are expected to be sig- nificant. We evaluated these emissions using the measured CO at the cities of Puebla (19.05 ◦ N, 98.2 ◦ W) and Toluca (19.29 ◦ N, 99.67 ◦ W), and concluded that the initial model underpredicts the observed CO levels inside the urban areas by a factor of ∼ 5 (Fig. S1, Supplement). Therefore the re- gional NEI emissions of CO outside of Mexico City have been increased by a factor of 5. This adjustment results in a small increase the regional background levels with a very minor effect on the Mexico City plume (Fig. S1, see Supple- ment). The increase in the regional CO levels of ∼ 50 ppb provides a slightly better agreement with the observed CO levels along the C130 flight track of 29 March 2006 (during a period with very low biomass burning, Aiken et al., 2010). The SOA treatment in the CHIMERE model that was pre- viously based on Pun et al. (2006) and Hodzic et al. (2009) for anthropogenic and biogenic VOC precursors, and on Hodzic et al. (2010a) for primary organic vapors, has been revised for the purpose of this study. SOA formed from anthropogenic and biomass burning precursors has been re- placed by the new empirical approach based on field mea- surements of SOA/1CO ratios. Besides the previous tradi- tional biogenic SOA (BSOA) from OH oxidation of isoprene and terpene precursors, an alternative parameterization has been included in the model in order to evaluate the differ- ences between current BSOA parameterizations and to ac- count for NO x -dependent BSOA yields. Anthropogenic and
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