Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 1 , and F. Minvielle 3 ´ discussions.cls. ees, 14 Avenue Edouard Belin, 31400 ´ e Lille 1, 59655 Villeneuve d’Ascq, . ´ en 1 , M. Mallet 3 ´ erique, Universit , V. Pont ´ 2 e X class copernicus ´ er E T A ´ erologie, Observatoire Midi-Pyr , B. Bessagnet 1 ´ e ´ er

Institut National de l’Environnement Industriel et des Risques, ParcLaboratoire Technologique Alata, d’A Laboratoire d’Optique Atmosph ([email protected])

Correspondence to: J. C. P 2 60550 Verneuil en Halatte,3 France. Toulouse, France. 1 with version 4.0 of the L Manuscript prepared for Atmos. Chem. Phys. Discuss. J. C. P Russian wildfires episode on photochemistry during the 2010 Influence of the aerosol solar extinction Date: 18 September 2015 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | up to 50 % (in day- 3 and O 2 daytime concentration and to an 2

2

for environmental policies. In the context of air quality monitoring, the exceedance of In consequence, efficient control strategies have now become a challenge ulate origin can have adverse health effects (Miller et al., 2012; Beelen et al., 2014). For several years, it has been well recognized that air pollution of gaseous and partic- 1 Introduction as ammonium, nitrates and sulphates. ozone and nitrogen dioxide as well as the formation of inorganic aerosol species such photolysis rates tend to improve the estimation of the near-surface concentration of ments at Moscow indicate that an explicit representation of aerosols interaction with In terms of model performance, comparisons of simulations with air quality measure- and secondary organics (4–10 %) when aerosol impact on photolysis rates is included. ied period, caused by a reduced formation of secondary aerosols such as sulphates concentration (PM10) is shown to be decreased by 1–2 %, on average during the stud- over the entire boundary layer, where aerosols are located. Also, the total aerosol mass ozone reduction near the surface of 1–12 %. The ozone reduction is shown to occur spatial extent, with a reduction of the photolysis rates of NO dicate an important influence of the aerosol solar extinction, in terms of intensity and on-line coupling between theaerosol optical chemistry-transport module) model and the CHIMERE radiative (extended transfer code by TUV. an Results of simulations in- 2010, which coincides to the peak of fire activity. The methodology is based on an rope during the 2010 wildfires episode is discussed for the period from 5 to 12 August In this work, impact of aerosol solar extinction on the photochemistry over eastern Eu- photolysis rates lead to a 3–15 % increase in the NO Abstract time average) along the aerosol plume transport. At a regional scale, these changes in

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15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ) and 2 3 ´ e et al., 2008) due to their negative impacts on ´ e et al., 2008; Menut et al., 2013). However, Real and Sartelet (2011)

´ e et al., 2008). Photochemical pollutants (ozone, secondary aerosols,...), which

tend to worsen air quality model performance in simulating ozone and particulate con- highlighted that simplified parametrization of aerosol impact on photolysis rates could sis rates (Honor often taken into account as simplified attenuation factors when evaluating the photoly- quality modelling platforms is that impacts of aerosols and clouds on solar radiation are To reduce computational time for operational purpose, one major characteristic of air search Observations (MILAGRO) campaign. centrations over Mexico City during the 2006 Megacity Initiative: Local and Global Re- 5–6 % in daytime ozone and secondary aerosols (nitrate, secondary organics) con- due to the presence of particles led to a decrease of about, respectively, 2–17 % and terest for air quality monitoring (Honor highlighted, with WRF-CHEM modelling experiments, that changes in photolysis rates volatile organic compounds (VOC) (Jenkin and Clemitshaw, 2000), are of particular in- ozone concentration over Hong-Kong during highly polluted days. Also, Li et al. (2011b) model, that aerosol solar extinction could lead to a 7–32 % reduction in maximum showed, by using a combination of remote sensing observations and chemical-transport lengths (Li et al., 2011a,b; Lou et al., 2014). For example, Wai and Tanner (2010) available actinic flux by interacting with solar radiation in the ultraviolet-visible wave- flux (Seinfeld and Pandis, 2006). Aerosols are known to have large influence on the the atmosphere is the photolysis rate, which mainly depends on the available actinic The key parameter that governs the photo-dissociation of photochemical precursors in both environment and human health (Amin, 2014; Hunova et al., 2014). the French national air quality(Honor forecasting and monitoring system knownare as formed PREV’AIR from photo-dissociation of precursors such as nitrogen dioxide (NO where the regional chemistry-transport model CHIMERE (Menut et al., 2013) is used in of these thresholds is evaluated from air quality numerical forecast such as in France a country to prevent people from air pollution exposure. In general, the exceedance certain thresholds of pollutant concentrations is a criterion often used by authorities of

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15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ´ e et al. ´ er ´ e et al., 2010), and the Tropospheric Ultra- 4 ´ er and volatile organic compounds) that can react in the atmosphere to 2

´ e et al. (2009, 2010). This mixing approach has been previously used by P

´ er extended by an aerosol optical module (P The approach is based on an on-line coupling between the regional model CHIMERE, latter impact is the subject of the present study. sity of solar radiation, which in turn could affect photochemistry of the atmosphere. The P reactions (Slade and Knopf, 2013; Nie et al., 2015). Finally, they can affect the inten- are first modelled by CHIMERE using an aerosol core-shell mixing hypothesis, as in directly affect air quality or indirectly by acting as a medium in complex heterogeneous ology, the aerosol optical thickness, single scattering albedo and asymmetry parameter form ozone and other pollutants (Turquety, 2013). They also released aerosols that can violet and Visible (TUV) radiation model (Madronich and Flocke, 1998). In this method- (2014) to study the 2010 Russian wildfires direct radiative forcing and its feedback on CO, OH, NO, NO atmospheric chemistry in several ways. They emit primary gaseous pollutants (such as tion, especially biomass burning particles, can affect photochemistry. Fires can affect case study represents an excellent opportunity to discuss how aerosol solar extinc- the contribution of smoke aerosols during this specific event is very large. Then, this This suggests that, even if anthropogenic aerosols are present over the studied region, than the one observed during typical August conditions over the period 2001–2010. the aerosol optical thickness over the Moscow region was more than three times larger study of Chubarova et al. 2012 clearly shows that, during this specific wildfire episode, (Zvyagintsev et al., 2010; Konovalov et al., 2011; Popovicheva et al., 2014). Also, the ondary aerosols and large concentrations of ozone, especially over this specific region at regional scale. We focus on2010 as a its major episode fire was event characterized that by occurred important in concentrations of during primary August and sec- the impact in terms of modelled ozone budget and the formation of secondary aerosols an explicit representation of the alteration of photolysis rates by aerosols and discuss The aim of the present study is to implement, in the chemistry-transport model CHIMERE, centration, especially under highly polluted environments.

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15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | E in o E to 57.30 o 5 N in latitude and from 18.70 o and secondary aerosols over Russia induced 3 ,O 2

N to 63.20 o

(OC and BC), secondary organic aerosols (SOA), sea salt, natural and anthropogenic 10 chemical species: sulphates, nitrates, ammonium, primary organic and black carbon longitude. The aerosol part is described by Bessagnet et al. (2004) and is composed of olution and ranges from 43.40 technique.fr/chimere/. In this work, the CHIMERE domain has a 30 km horizontal res- (Menut et al., 2013) and its documentation can be downloaded at http://www.lmd.poly- et al., 2013). The dynamics and gas phase parts of the model is regularly improved centrations of numerous gaseous and particulate pollutants (Vautard et al., 2001; Menut CHIMERE is a state-of-the-art 3D chemistry transport model that calculates the con- 2.1.1 Aerosol module 2.1 Description of the CHIMERE model 2 Methodology near surface concentrations of NO conclusions and perspectives of future works are given in Section 4. their on-line coupling. In Section 3 areby discussed modifications modelled of regional photolysis changes rates in by the smoke aerosols during August 2010. Finally, Section 2 describes the configuration of each model as well as the development of on modelled photolysis rates and photochemistry. physical-chemically resolved aerosols with the actinic flux and the associated impact the formation of ozone andis the secondary use particles. of The two advantage specific of state-of-the-art such models to methodology explicitly simulate the interaction of to evaluate the impact of aerosol short-wave solar extinction on photolysis rates and time, aerosol optical properties are used as inputs in the radiative transfer code TUV tation of the absorption properties of particles during this specific period. In a second the regional atmospheric dynamics. Results indicate that it can give a good represen-

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15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ´ e et al. (2014) showed that ´ er 6 m in diameter) and includes the main physical processes µ

´ e et al. (2011). It has 27 vertical levels from 40 m to about 20 km and

´ er

tion as in P at a 30 km resolution. The version 3.1 is used in this study with the same configura- taine et al., 2004), respectively. The evaluation study of P CHIMERE is off-line driven by the Weather Research and Forecasting model (WRF) (Horowitz et al., 2003) and LMDzT–INCA global chemistry-transport models (Hauglus- ing the studied period, suggesting a low influence of these boundary conditions. Also, the 2000–2004 period, of the main gases and particles provided bymodel the have MOZART been shown to well capture the evolution of the Russian fire plume dur- CHIMERE is forced at these boundaries by monthly climatologies, calculated over the fire inventory of Kaiser et al. (2012) used in this work combined with the CHIMERE Kaiser et al. (2012). as well as a validation study for the 2010 Russian wildfires episode can be found in factors to estimate biomass burning emissions. More information on the methodology assimilation System combined with the use of specific combustion rate and emission vations from the Moderate Resolution Imaging Spectroradiometer into the Global Fire validated by Kaiser et al. (2012). It consists in the assimilation of the fire radiative obser- affecting Russia during 2010 are taken into account following the work described and from Nature (MEGAN) (Guenther et al., 2006). Aerosols and gases emitted by wildfires from vegetation are calculated using the Model of Emissions of Gases and Aerosols gas particle partitioning schemes (Bessagnet et al., 2008). VOC and NO emissions oxidation processes of relevant precursors of biogenic and anthropogenic origin and to the methodology of Vautard et al. (2005). SOA formation is represented through been used. Natural soil dust are dynamically produced within the domain according Anthropogenic emissions of gaseous and particulateConcerning origin come OC from the and EMEP database. BC emissions, the inventory of Junker and Liousse (2008) has (from about 40 nm to 10 and dry deposition and scavenging. dust and water. The evolution of aerosols issuch as described nucleation, with coagulation, condensation/evaporation, a adsorption/desorption, wet 8-bins size distribution

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15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ´ e et al., ´ er ´ e et al. (2010). To com- ´ er

7

A detailed evaluation of the optical module for the 2010 Russian wildfire episode by et al. (1996). Single Scattering Albedo (SSA) and asymmetry parameter (g), are calculated as in Wu absorbing properties of aerosols during the 2010 Russian wildfire episode (P needed in radiative transfer modelling, such as the Aerosol Optical Thickness (AOT), McMeeking et al., 2011). Also, such mixing has been shown to correctly reproduce the influencing aerosol population. The optical properties of the total aerosol distribution ings of secondary particles on black carbon aerosols over Europe (Vester et al., 2007; the shell can vary during the simulation in function of the different physical processes and water. This mixing choice is supported by recent studies giving evidence of coat- tering and absorption coefficients. It should be noted that the volume of the core and of secondary ones (sulphates, nitrates, ammonium, secondary organics) and sea salt the Mie algorithm for n-layered spheres of Wu and Wang (1991) to calculate the scat- been chosen with a core of primary species (BC, OC and dust) surrounded by a shell tive index of the core and the shell (Lesins et al., 2002) which is then used as inputs in pute the complex refractive index of a particle, the hypothesis of a core-shell mixing has 2014). For each size bin, a volume average procedure is used to calculate the refrac- description of this optical module is presented in the work of P tions, size distribution and chemical composition modelled by CHIMERE. A complete cal scheme dedicated to calculate aerosol optical properties from aerosol concentra- how aerosols will interact with the actinic flux. In that sense, we developed a numeri- of their impacts on photolysis rates and photochemistry as they provide information on The calculation of optical properties of particles is the pre-requisite for the evaluation 2.1.2 Modelling aerosol optical properties Yonsei University planetary boundary layer scheme (Hong et al., 2006; Hong, 2007). tion (Kain, 2004), the NOAH land surface module of Chen and Dudhia (2001) and the Hong et al. (2006) for the microphysics module, the Kain–Fritsch cumulus parametriza- includes the following parametrizations: the WRF single-moment five-class scheme of

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20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ´ e et al. (2014). Only a sum- ´ er

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(0.4–0.7 at 440 nm) on 11–12 August when the intense aerosol plume leaves the re- 5 August to 2–4 between 6 and 10 August. Then AOT decreases to moderate values when the plume overpasses the area, with an AERONET AOT (440 nm) from 0.56 on can see that a large enhancement of the particulate pollution is detected over Moscow has been recorded in the AOT measurements of the Moscow AERONET station. We transport of this intense aerosol plume over Moscow between 6 and 10 August 2010 tency, as discussed in further details hereafter on Figure 8. Figure 2 indicates that the be below 5 km and comparisons between CHIMERE and CALIOP show good consis- photolysis rates discussed on Figures 3 and 4. The altitude of transport was shown to of the aerosol solar extinction simulated by CHIMERE and its potential impact on the near the source region. These AOT biases may induce local under or overestimation such as local AOT underestimations within the intense plume or some overestimations of the day. Some minor discrepancies between CHIMERE and MODIS can be seen, spatial correlation of 0.4–0.8 and a normalized mean bias of -(15–40) % depending plume features in terms of transport and intensity during this specific period, with a mated by CHIMERE, we can see that the model is able to reproduce the main aerosol 10–12 August. Although the maximum AOT value observed by MODIS is underesti- Moscow and the northern part of the area (6–10 August) and back to the east on was advected in the anticyclonic flow from the source region (east of Moscow) towards large areas and values up to 4 along the transport of the aerosol plume. This plume highlight this intense particulate pollution episode with AOT (550 nm) above 1 over tensive wildfires and anthropogenic origin (Witte et al., 2011). MODIS observations central Russia which favored the re-circulation and accumulation of pollution from in- meteorological conditions were characterized by an important anticyclonic system over The simulated 850 hPa wind is also indicated. As shown by the 850 hPa wind fields, MODIS (Moderate Resolution Imaging Spectroradiometer) satellite sensor at 550 nm. and 12 August 2010 modeled by CHIMERE at 500 nm and measured by the Terra using different sets ofup measurements is is presented given by here. P Figure 1a-b presents the temporal evolution of the AOT between 5

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15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 9 ´ e et al. (2014) showed that organics species are the dominant part

´ ´ er e et al., 2014), which is the pre-requisite to evaluate its influence on

´ er

photolysis rates and the formation of photochemical pollutants. properties (P an appropriate representation of the aerosol size distribution and scattering/absorption aerosol simulation and measurements data highlighted the ability of the model to give ganic species with a low fraction of black carbon. Globally, the comparisons between aerosol composition over Moscow during the 2010 fire episode is dominated by or- Popovicheva et al. (2014) highlights, with physical-chemical measurements, that the Chubarova et al. (2012) and are typical of fires and smoldering conditions. Also, (0.95 in the visible spectrum) have been measured during this specific fire episode by large proportion of organic species is supported by recent studies. High SSA values Moscow (0.95–0.96 between 440 nm and 1020 nm). Such elevated SSA associated to tween 300 nm and 1000 nm), in good agreement with AERONET measurements over lead to high SSA modeled over Moscow throughout the period, with values of 0.97 (be- lower fraction (0.4–0.8 %). This important contribution of scattering organic aerosols chemistry favored by persistent sunny conditions. BC particles are present in a much wildfires with also an anthropogenic contribution) combined with an important photo- the result of large OC and VOC (Volatil Organic Compounds) emissions (mainly from plume moves away from Moscow. These elevated proportions of organic carbon are (43–67 %) while SOA dominates at the end of the period (71–75 %) when the aerosol ondary organic aerosols. OC is the major chemical species between 5 and 10 August butions of 8–67 % and 16.5–75 % for, respectively, primary organic carbon and sec- of the aerosol composition simulated by CHIMERE over Moscow with relative contri- study period, P cies in simulating the transport of the intense aerosol plume over Moscow. During the these two days, the model underestimation is of 60–75 % due to some model deficien- during this period with biases from -53 % to 8 %, except for the 6 and 10 August. For gion. CHIMERE simulates rather well the temporal evolution of the AOT over Moscow

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15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | (1) ) and the 2 ) the actinic flux λ ). The absorption cross sec- 1 − .nm 1 − .s 2 − ) is calculated as follows: 1 10 − (photons.cm dλ ) 2 λ λ ( .F ) and 1 λ λ,T ,T) are, respectively, the absorption cross section (cm ( λ ( .φ φ ) λ,T ( σ 2 ,T) and 1 λ Z λ λ (

σ ) =

1

− s

( ation is calculated by using their respective aerosol optical thickness, single scattering but also by the presence of clouds and aerosols. For clouds and aerosols, the attenu- atmosphere, the actinic flux can be attenuated by molecular absorption and diffusion sidering 5646 wavelengths between 120 nm and 1250 nm. When going through the The actinic flux is calculated by integrating the solar flux over all sphere angles con- model WRF used to drive CHIMERE. TUV by using the vertical profile of air temperature issued from the meteorological photon. The dependence of both parameters on the air temperature is calculated by quantum yield is the probability that the molecule is dissociated after collision with a tion reflects the probability of collision between a photon and the molecule, while the

where quantum yield of abetween given wavelengths molecule, T the air temperature (K) and F( J

The photolysis rate of a given specie J (s controls the abundance of numerous air pollutants such as ozone and nitrogen dioxide. by short-wave solar radiation. This process is very important in the atmosphere as it Photolysis is the process breaking the covalent bond of some reactive gaseous species website: http ://cprm.acd.ucar.edu/Models/TUV/. The modeland photolysis calculates rates the of actinic a flux large number of photochemical species. we used the version 4.6 of the code (released in March 2009) freely available at the tional Centre for Atmospheric Research (Madronich and Flocke, 1998). In this study, TUV is a widely-used state-of-the-art radiative transfer model developed at the Na- 2.2 Description of the TUV model

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Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 11

been implemented within CHIMERE so that each model runs simultaneously. During between TUV and CHIMERE. In this approach, the radiative transfer code TUV has The methodology developed in this study consists of a one-way and on-line coupling 2.3 Simulation set-up aerosols during the 2010 Russian wildfires presented hereinafter. idation study gives confidence in our estimation of photolysis rates perturbations by at the surface and in the lower troposphere over this highly polluted area. This val- They highlighted the good performance of the model in reproducing observations both model and UV actinic flux measurements over Mexico during the MILAGRO campaign. Recently, Palancar et al. (2013) realized a intercomparison exercise between the TUV elled radiative fluxes (Joseph et al., 1976). approximation has been chosen in TUV as it allows an accurate estimation of mod- equation and compute the actinic flux along the atmospheric column, the Eddington terpolated to the TUV wavelength grid (120–1250 nm). To solve the radiative transfer 200, 300, 400, 500, 600 and 700 nm using the aerosol optical module and then in- Concerning aerosols, the three optical properties (AOT, SSA and g) are calculated at and photolysis rates (Lau and Kim, 2012). during the studied period suggest a low impact of clouds on the modelled actinic flux our approach. However, the anticyclonic conditions that prevailed over eastern Europe the activation of aerosols into cloud condensation nuclei are not taken into account in Flocke, 1998). It should be noted that changes in the cloud optical properties due to asymmetry parameter are considered constanttaken equal in to, the respectively, 0.99 UV–visible and wavelengths and 0.85 for are the three types of clouds (Madronich and are estimated by the meteorological model WRF. The single scattering albedo and altitude clouds. Altitudes of their bases and tops as well as their optical thicknesses mogeneous layers and are considered to be of three types : low, middle and high albedo and asymmetry parameter. In TUV, clouds are assumed to be horizontally ho-

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15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | (4) (3) (2) photolysis rates, which mainly 3 photolysis: 2 and O ] 2 2 12 NO ] [ and OH radicals in the troposphere. Indeed, 3 J 2 O [ J P) with a dioxygene molecule (M is a third body favouring 3 ) M P + 3 ) ( 3 D O O 1 ]. In parallel, the major sink of ozone during daytime is its photo- ( + 2 O −→ + NO 2 M O + −→ 2 −→ O .ϑ ~

.ϑ ) + ~ +

2 P + 3

( 3 O constant rate J[NO dissociation following the reaction: Given that reaction (3) is rapid, the formation rate of ozone is mainly determined by the O

the reaction): followed by the reaction of O(

We will focus on the aerosol impact on NO induces a computation time increase of 50 % compared to the simulation (1). It should be noted that adding the aerosol impact on solar extinction in simulation (2) chemical pollutants are then estimated by differencing the two simulations: (2) - (1). The impact of aerosols on photolysis rates and associated concentrations of photo- ysis rates calculation: CHIMERE–TUV(gases+clouds+aerosols). (2) In the second one, the impact of aerosols on solar extinction is added in the photol- CHIMERE–TUV(gases+clouds). (1) In the first one, the attenuation of actinic flux is only due to gases and clouds: photochemical pollutants. Two simulations are performed for the period of peak fire activity (5–12 August 2010): estimated by TUV are in turn used by CHIMERE to calculate the concentrations of influence of aerosol solar extinction on photolysis rates. Then, the photolysis rates mixing (AOT, SSA, g) are used as inputs in TUV in order to take into account the the simulation, the aerosol optical properties modelled by CHIMERE for a core-shell the major source of ozone is the result of the NO NO drives the concentration of ozone, NO

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10 15 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | (5) ], for each day 2 and VOC, which can result 2 ] than for J[NO 3 , NO 2 13 , respectively. Changes are shown to be negative over 3 and O 2 OH 2 −→ O 2 H

) + and nitrogen dioxyde

D D) will rapidly react with a water molecule to form OH radicals: 1 1

( and Sartelet (2011) in which they simulate, by using the chemistry-transport model These modelled changes obtained here are comparable with the recent study of Real tween 6 and 10 August 2010. This point will be discussed in further details hereafter. region has also been affected, especially during the arrival of the aerosol plume be- the transport of the aerosol plume (20–50 %). The photochemistry over the Moscow of the studied period. For both photolysis rate, the largest reduction is simulated along the aerosol solar extinction is more pronounced for J[O photolysis rates of NO the AOT spatial features (see Figures 1a-b). It is interesting to note that the impact of Figures 3a-b and 4a-b report the daytime average percentage changesthe in near entire surface area with mean daytime values between -2 % and -50 % and closely follow fected significantly the UV-visible solar radiation in terms of intensity and spatial extent. During the wildfire episode, the important concentrations of scattering aerosols have af- 3.1 Regional impact of the 2010 Russian wildfires on the formation of ozone 3 Results and discussion with the OH radical. sequence of reactions (R1 to R4) is generally initiated by the reaction of various VOC in the formation of, respectively, sulphate, nitrate and secondary organic aerosols. The O For example, they contribute to the oxidation of SO volved in the formation of secondary particles as oxidants of their gaseous precursors. O( The latter reaction is a major source of OH radicals in the troposphere. They are in-

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15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | AOT(550 nm) ´ e et al., 2014) < ´ er ], due to the aerosol ] in the presence of 2 3 ] (source of ozone, see 2 ] associated to an intense 2 ] and J[O 2 concentration is simulated, as it is 2 ] reduction seems to slightly dominate the 2 14 ] (sink of ozone, see equation 4). We can de- 3 photolysis reduction during the 2003 European sum- 2 ] due to aerosols (between 2 and 50 %) leads to an increase of 2 ] reduction, resulting in a decrease of the near surface concentration ] reaching 30 % (in monthly mean) during summer 2001 over Euro- 3 3 . Some notable modification of the NO 3

] and J[O 2 and O

2 2.5). The low absorbing properties of the Russian smoke plume (P

70 % associated to similar aerosol loadings as obtained in our study (1 showed, over , a reduction of maximum ozone concentration reaching 30 % to polluted Asian regions. For example, Bian et al. (2007) and Wai and Tanner (2010) Such impacts are however less pronounced than the ones obtained over some highly aerosol plume over Mexico City, resulting in a 5–10 % diminution of ozone production. < campaign during March 2006, a 40 % attenuation of J[NO bining STEM-2K3 model experiments and aircraft observations from the MILAGRO solar extinction, reached 30 %. Also, Mena-Carrasco et al. (2009) highlighted, by com- centration (for July 2001) over areas where the decrease of J[NO Real and Sartelet (2011) who simulated a 4–8 % reduction of near-surface ozone con- influence of J[O of ozone between 1 % and 12 %. These results are comparable to those obtained by

(2007) simulated a 15–30 % NO duce from figure 5 that the influence of J[NO pean regions characterized by elevated AOT (0.6–0.7 at 550 nm). Also, Hodzic et al. NO J[NO According to equations 2 to 4, theFigure alteration 5 of gives J[NO an example of these corresponding changes during the 8 August for Polyphemus-Polair3D coupled with the radiative transfer code Fast-J, a reduction of mer heatwave in case of absorbingSSA biomass (532 burning nm) aerosols (AOT(550 = nm) 0.83–0.87). = 0.7–0.8, aerosols suggests, in turn, a modification of their concentrations near the surface. equations 2 and 3) and variations of J[O

tant diminution of J[NO mainly driven during daytime by its photolytic destruction (see equation 2). The impor- daytime concentration is influenced by both variations of J[NO its near surface concentration reaching, in average, 3 to 15 %. Concerning ozone, its

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15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ) 2 ] (re- 2 ] is more sensitive to 3 15

concentration of 3 % (per unit of AOT). Response of 2

onists responses : (1) Increase of NOx concentration trough reduction of photolysis case, inclusion of the aerosol radiative impact on photochemistry leads to two antag- studied period, with a VOC(ppmC)/NOx(ppm) ratio always below this threshold. In this Figure 7 indicates that such photochemical regime occurred over Moscow during the nisms, a VOC(ppmC)/NOx(ppm) ratio below 4 defines a NOx-saturated environment. and Pandis, 1998). Based on the study of Dodge (1977) on ozone chemical mecha- concentrations of VOC and NOx : A NOx-limited and a NOX-saturated regime (Seinfeld possible to identify two regimes of ozone formation by looking at the ratio between the and volatile organic compounds (VOC) in a complex photochemistry. However, it is

ozone formation is driven by two major precursors: nitrogen oxides (NOx = NO + NO the ozone concentration under the aerosol radiative influence is more complex. Indeed, in an increase of the ground NO duction of about 6 % per unit of AOT). These modifications of photolysis rates result the presence of particles (reduction of about 10 % per unit of AOT) than J[NO

loading increases. As shown previously over the entire area, J[O a correlation of 0.90–0.95, i.e modifications become more important when the aerosol nm). As expected, changes appear to have a good linearity with AOT (440 nm) with surface photolysis frequencies and concentrations as a function of modelled AOT (440 Moscow is discussed in terms of daytime average percentage changes in their near- On Figure 6, the impact of particles on the formation of ozone and nitrogen dioxide over 3.2 Impact of the 2010 Russian wildfires on the photochemistry over Moscow August 2010). Gaseous andstation will particulate also measurements be used from in the the analysis. Moscow air quality solar extinction is pronounced, especially during the aerosol plume overpass (6–10 ondary particles, we will now focus our study on the Moscow region where the aerosol To further investigate aerosol feedback on the ozone cycle and the formation of sec- could be a reason for such a behaviour.

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15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 16 at an altitude of 200 m), suggesting a prevail- 1 − ) modeled by CHIMERE and retrieved by CALIOP for the 1 − simulated with and without aerosols and measured at Moscow by an air 3

, indicating a low altitude transport. Above, CALIOP aerosol extinction gradually and O

1

2 −

values and daily maximum values, respectively. We can see that, for both configura- quality station has been made. Results are presented in Tables 1 and 2 for hourly NO For such analyse, statistical comparisons between the near-surface concentrations of tion of photochemical pollutants, compared to a simulation without aerosol feedback. aerosol impact on photolysis rates tend to improve the simulation of the concentra- In terms of model performance, it is interesting to see if an explicit representation of altitude. km where most of the aerosol extinction occurs and then gradually decreases with the presence of the intense aerosol plume, is maximum (4–5 %) below an altitude of 2 estimated impact of aerosols on the ozone reduction. This ozone reduction, due to the within the uncertainty range of measurements for both cases, giving confidence in the ing anthropogenic origin. CHIMERE compares well with CALIOP extinction coefficients extinction (maximum value of 0.15 km tense fire plume, particles remain confined near the ground, with a much lower aerosol km decreases to become negligible at an altitude of 5 km. For comparison, outside the in- sured below the first two kilometres of the atmosphere with values reaching 0.5–0.95 see that inside the intense fire plume, more than 70 % of the aerosol extinction is mea- in the ozone concentration due to this intense aerosol plume is also indicated. We can tions of these 2 points). The vertical profile of the daytime average percentage changes 9 August inside and outside the intense aerosol plume (see Figure 1 for the localisa-

extinction coefficient (in km The influence of aerosolsalso on in the photochemistry low does troposphere, as not illustrated only in occur Figure at 8. This the figure surface presents but the aerosol responses, about 1 % per unit of AOT (see Figure 6). pact of aerosols on the ozone concentration is then small due to these two antagonist (2) reduction of the ozone photolysis is favourable to its accumulation. The overall im- rates is unfavourable to ozone formation in a NOx-saturated environment. In parallel,

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15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 2 2 on 2 and NO 3 for the RMSE and of 0.22–0.60 3 g/m µ ) may also influence actinic flux through 2 17 are of 48-88 2 ) modelled with and without aerosol feedback along with cor- 3 g/m µ

account for, respectively, 70 % and 25 % of actinic fluxes reduction observed

2

models (including CHIMERE) and EMEP measurements, also showed a model NO intercomparison study between several European state-of-the-art chemistry-transport study by Palancar et al. (2013) estimated the relative influence of aerosols and NO at the surface. Hence, such results suggest a moderate impact of the O Indeed, it should be noted that Bessagnet et al. (2014), who performed an extensive rates as gaseous pollutants (especially NO no such measurements are available to us for this specific event. However, a recent NO certainties in the EMEP anthropogenic emission inventory used in the present study. The model biases on these two species can induce a bias on theulated modelled values photolysis of actinic flux with observations, which is not possible for this study as over Mexico City with TUV model calculations. Comparisons indicate that aerosols and tions, scores for ozonefor and the NO temporal correlation. Such biases could be the consequence of possible un- and ozone underestimation over Europe in the frame of the EURODELTA IIIdirect project. absorption. Unfortunately, quantifying this bias would require to compare sim- the actinic fluxes by comparing measurements made during the MILAGRO campaign Depending on the day, the model simulates lower or higher hourly values compared to 9 August), which leads to slightly reduce the bias between model and observations. a maximum diminution reaching 7–10 % during the aerosol plume overpass (7, 8 and moderate overall impact of the aerosol solar extinction on the ozone production, with responding observations at the Moscow monitoring station. This figure confirms the concentration (in plays the temporal evolution (between 5 and 12 August 2010) of the near-surface ozone To further investigate the aerosol feedback on the ozone daytime cycle, Figure 9 dis- both species and for both hourly and maximum values. simulation improves the correlation and slightly reduces biases with measurements for fires episode. Overall, Tables 1 and 2 indicates that the inclusion of aerosols in the CHIMERE biases on the photolysis rates simulated over Moscow during the 2010 wild-

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25 20 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | , in- 3 ´ e et al. and O ) and SOA 2 2

18

mating its dry deposition and titration by NO, as previously highlighted by Honor concentrations over the period, which could be due to uncertainties in correctly esti- a possible reason for these biases. Also, the model is shown to overestimate nighttime it is obvious that thisviously, process uncertainties does on not the entirely EMEP explain emission model database biases. for As this indicated specific pre- region could be tolysis rates could improve the estimation of ozone formation for some days. However, these processes, adding the aerosol direct radiative impact on the simulation of pho- processes are missing and/or not well represented in the CHIMERE model. Among observations. The ozone model biases presented on Figure 9 clearly show that some in the near-surface concentrations of sulphates (oxidation product of SO particulate pollution over, respectively, Europe and Mexico City. As for NO formation of secondary aerosols. As illustrated in figure 10a, the maximum reduction mation of secondary aerosols due to the aerosol solar extinction, in case of intense closer to the observed one. However, the correlations are not always improved when sphere (through reduction of OH radicals, see equation 5), which leads to decrease the and Sartelet (2011) and Li et al. (2011b) who showed a 5–10 % reduction of the for- is slightly decreased and the simulated concentrations of ammonium and nitrates get In parallel, the presence of aerosols tends to reduce the oxidising capacity of the atmo- the entire period (Figure 10a). These results are comparable to the findings of Real tematically reduced (see Table 3). The large overestimation of sulphate concentrations the nocturnal air ventilation could also be a reason for such a model bias. of the total aerosol mass concentration (PM10) comprised between 1 and 2 % over formation of secondary inorganic species in the CHIMERE model with a RMSE sys- (2008) over Western Europe. It should be noted that a inadequate representation of tween 40 nm (bin 1) and 300 nm (bin 4). The overall impact is then a slightly reduction cluding the optical effect of aerosols in the photolysis calculations slightly improves the due to a reduced formation of very fine particles, i.e with a diameter comprised be- and 4 %, respectively. For this day, figure 10b shows that these changes are mainly (oxidation product of VOC) occurs on 8 August with daytime average values of 10 %

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10 25 15 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ´ e et al., ´ er

19

is detected over Moscow when the plume overpasses the area, with an AERONET and CALIOP show good consistency. A large enhancement of the particulate pollution titude of transport was shown to be below 5 km and comparisons between CHIMERE total chemical composition modelled over Moscow during the study period (P and intensity (normalized mean bias of -(15–40 %)) during this specific period. The al- impact on photolysis rates as this chemical specie represents less than 10 % of the the main aerosol plume features in terms of transport (spatial correlation of 0.4–0.8) ing sulphates particles is expected to have a low influence on the estimation of aerosol tense fire plume transported in the anticyclonic flow. The model is able to reproduce taking into account the aerosol radiative influence. The large overestimation of scatter- episode with AOT (550 nm) above 1 over large areas and values up to 4 along the in- particulate pollutants. MODIS observations highlight this important particulate pollution with and without aerosol impact on photolysis rates and concentrations of gaseous and 5 to 12 August 2010, corresponding to the peak of fire activity, have been performed tochemistry over eastern Europe during the 2010 wildfires episode. Simulations from diative transfer code TUV to study the impact of aerosol solar extinction on the pho- transport model CHIMERE (complemented by an aerosol optical module) and the ra- In the present study, we have developed an on-line coupling between the chemistry- 4 Conclusions

environments. tion can improve the model capacity to reproduce the photochemistry under polluted suggests that taking into account the aerosol solar extinction in the photolysis calcula- ancies between measurements and model simulation results can be present, Table 3 the determination of particle’s interaction with the actinic flux. Even if some discrep- 2014). This is confirmed bySSA the during excellent this agreement between specific modelled event and (as measured discussed in section 2.1.2), which is a key factor in

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15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 3 of 3–15 % 2 20 ] comprised between 2 % and 50 %, the maximum 3 ] (reduction of about 6 % per unit of AOT), resulting in an 2 concentration of 3 % (per unit of AOT) and a small reduc- 2 production near the surface comprised between 1 % and 12 ] and J[O 3 2

] is more sensitive to the presence of particles (reduction of about 10 3

of the total particulate concentration (PM10) of 1–2 % on average over the period. of sulphates and secondary organics up to 4–10 %, which result in a small reduction tion. Over Moscow, the aerosol plume tends to decrease the daytime concentrations on the formation of secondary aerosols, through the modification of the OH concentra- along the boundary layer where aerosols areIn located addition, with, the for impact example, of a aerosols 4–5 on % photolysis O rates is shown to have an influence tion of ozone of 1 % (per unitreduction of modelled during AOT). 9 The August photochemistry within is the first shown two to km be of impacted the atmosphere.

increase of the ground NO and a decrease in the O indicate that J[O % per unit of AOT) than J[NO the arrival of the aerosol plume between 6 and 10 August 2010. Over this area, results The photochemistry over the Moscow region has also been affected, especially during % during 8 August. quencies result in an regional increase in the daytime concentration of NO reduction being modelled in the aerosol plume. These modifications of photolysis fre- mean reduction of J[NO The impact of aerosols on photolysis rates is shown to be regionally significant with a measurements over Moscow (0.95–0.96 between 440 nm and 1020 nm). values of 0.97 (between 300 nm and 1000 nm), in good agreement with AERONET tribution), which lead to high SSA modeled over Moscow throughout the period with large OC and VOC emissions (mainly from wildfires with also an anthropogenic con- ing the transport of thedominant intense part aerosol of the plume aerosol over composition Moscow. simulated Organics by species CHIMERE are over the this area due to the model underestimation is of 60–75 % due to some model deficiencies in simulat- with biases from -53 % to 8 %, except for the 6 and 10 August. For these two days, simulates rather well the temporal evolution of the AOT over Moscow during this period AOT (440 nm) from 0.56 on 5 August to 2–4 between 6 and 10 August. CHIMERE

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15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ´ e, C., Liousse, C., 21 Authors are grateful to the CRI at Lille 1, Thieuleux Franc¸ois at LOA and

and Rouil, L.: Aerosolscale, modeling Atmospheric with Environment, CHIMERE 38, — 2803–2817, Preliminary 2004. evaluation at the continental tored concentrations, Water, Air and Soil Pollution, 225, 1–9, 2014. to air pollutionmulticentre on ESCAPE natural-cause project, mortality: The Lancet, an 383, analysis 785–795, 2014. of 22 European cohorts within the

Amin, N.: Effect of ozone on the relativeBeelen, yield R., of Raaschou-Nielsen, O., rice Stafoggia, crop M., and in co Japan authors: evaluated Effects of based long-term on exposure moni- Bessagnet, B., Hodzic, A., Vautard, R., Beekmann, M., Cheinet, S., Honor References

french spatial agency is acknowledged for its financial support. would also like to thank Isabelle Chiapello at LOA for her fruitful scientific discussion. The CNES is acknowledged for providing the surface air quality measurements used in this study. Authors Acknowledgements. Anthony Ung at INERIS for their technical support. Olga Kislova at Mosecomonitoring (Moscow) chemistry at regional and urban scale. to investigate the role of enhanced UV absorption by secondary organics on photo- Saleh et al., 2014). The methodology developed in this study provides a powerful tool ation, especially at the shorter visible and UV wavelengths (Zhong and Jang, 2011; Recently, it has been suggested that some organic aerosols can absorb solar radi- species such as ammonium, nitrates and sulphates. interaction with photolysis rates tend tocentration improve of the ozone estimation of and the nitrogen near-surface dioxide con- as well as the formation of inorganic aerosol air quality measurements at Moscow indicate that an explicit representation of aerosols sets of observations. In terms of model performance, comparisons of simulations with with those obtained in recent studies by combining model experiments and different The results presented in this work, issued from a modelling exercise, are consistent

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15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ´ eorologie Dynamique general ´ et 22

of entrainment processes, Monthly Weather Review, 134, 2318–2341, 2006. Soc., fall conference, Seoul, Korea, Oct. 25-26, 2007. ticulate matter in Europetransport during and radiative summer effects, 2003: Atmospheric meso-scale Chemistry modeling and Physics, of 7, smoke 4043–4064, emissions, 2007. circulation model: description and backgroundGeophysical tropospheric Research, chemistry 109, evaluation, d04314.doi:10.1029/2003JD003957, Journal 2004. of of global terrestrial isopreneAerosols from emissions Nature), using Atmospheric MEGAN Chemistry and (Model Physics, of 6, 3181–3210, EmissionsHolland, 2006. of E. A.: Gases Interactive and chemistry in the Laboratoire de M precursor relationships, in: ProceedingsOxidant of Pollution and the its International Control, Conference pp. 881–889, on 1977. Photochemical concentration in Tianjin, China, Atmospheric Environment, 41, 4672–4681, 2007. State / NCAR MM5Wea. modeling Rev., 129, system. 569–585, Part 2001. 1: Model description andits implementation, radiative Mon. effects duringMeas. extreme Tech., 5, fire 557–568, event 2012. over Central Russia in summer 2010, Atmos. evaluation with observationsmeasurements issued in from Feb/Mar 2009, the Technical EMEP 2009 report, 2014. EMEP intensive period and standard Pun, B., Seigneur,over Europe–focus C., on secondary anddOI:10.1007/s10874–009–9129–2, organic 2008. Schulz, aerosols, Journal M.: of Atmospheric Regional Chemistry, modeling 61, of carbonaceous aerosols

Hong, S. Y., Noh, Y., and Dudhia, J.: A new vertical diffusion package with an explicit treatment Hong, S. Y.: Stable boundary layer mixing in a vertical diffusion scheme, The Korea Meteor. Hodzic, A., Madronich, S., Bohn, B., Massie, S., Menut, L., and Wiedinmyer, C.: Wildfire par- Hauglustaine, D. A., Hourdin, F., Jourdain, L., Filiberti, M. A., Walters, S., Lamarque, J. F., and Guenther, A., Karl, T., Harley, P., Wiedinmyer, C., Palmer, P. I., and Geron, C.: Estimates Dodge, M. C.: Combined use of modeling techniques and chamber data to derive ozone Chen, F. and Dudhia, J.: Coupling an advanced land-surface / hydrology model withChubarova, the N., Penn Nezval, Y., Sviridenkov, I., Smirnov, A., and Slutsker, I.: Smoke aerosol and

Bian, H., Han, S., Tie, X., Sun, M., and Liu, A.: Evidence of impact of aerosols on surface ozone Bessagnet, B., Colette, A., Meleux, F., and co authors: The EURODELTA III exercise–Model Bessagnet, B., Menut, L., Curci, G., Hodzic, A., Guillaume, B., Liousse, C., Moukhtar, S.,

5

30 25

20 10 15 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 23

´ e, C., Rouil, L., Vautard, R., Beekmann, M., Bessagnet, B., Dufour, A., Elichegaray, C.,

of hydrometeorological extremes, J. Hydrometeor., 13, 392–403, 2012. J. J., Razinger, M.,emissions Schultz, estimated with M. a G.,power, global Biogeosciences, Suttie, fire 9, M., assimilation 527–554, system 2012. and based van on der observed Werf, firespheric G. radiative impacts R.: of Biomass thean burning 2010 extreme air Russian pollution wildfires: episode11, integrating in 10 the modelling 031–10 Moscow 056, and region, 2011. measurements Atmospheric Chemistry of and Physics, 181, 2004. record of fossil fuel andistry biofuel and Physics, consumption 8, for 1195–1207, the 2008. period 1860-1997, Atmospheric Chem- radiative flux transfer, Journal of the Atmospheric Sciences, 33, 2452–2459, 1976. Flaud, J. M., Malherbe, L., Meleux,son, F., Menut, N.: L., Predictability Martin, of D., Peuch, European A., airand Peuch, quality: V. H., analyses Assessment and of Pois- by 3 yearsdoi:10.1029/2007JD008761, the of 2008. operational PREV’AIR forecasts system, Journal of GeophysicalTie, X., Research, Lamarque, 113,D04301, J.related F., and tracers Schultz, : M. Description G.:Research, and 108, A evaluation 108(D24), global of 4784, simulation MOZART, 2003. of version tropospheric 2, ozone Journal and ofhealth outcomes Geophysical in Prague, International86, archives 89–97, of occupational 2014. and environmental health, chemical processes governing their formationEnvironment, 34, in 2499–2527, the 2000. planetary boundary layer, Atmospheric

Lau, W. K. M. and Kim, K.-M.: The 2010 Pakistan flood and Russian heat wave: teleconnection Konovalov, I. B., Beekmann, M., Kuznetsova, I. N., Yurova, A., and Zvyagintsev, A. M.: Atmo- Kaiser, J. W., Heil, A., Andreae, M. O., Benedetti, A., Chubarova, N., Jones, L., Morcrette, Kain, J. S.: The Kain-Fritsch convective parameterization: An update, J. Appl. Meteor., 43, 170– Junker, C. and Liousse, C.: A global emission inventory of carbonaceous aerosol from historic Joseph, J. H., Wiscombe, W. J., and Weinman, J. A.: The delta-Eddington approximation for Horowitz, L. W., Walters, S., Mauzeralles, D. Z., Emmonds, L. K., Rash,Hunova, P. I., J., Maly, Granier, M., C., Rezacova, J., and Branis, M.: Association betweenJenkin, ambient M. ozone E. and and Clemitshaw, K. C.: Ozone and other secondary photochemical pollutants: Honor

5 25 30

20 10 15 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ¨ a, T., Kulmala, M., and Fu, C. B.: Influence of ¨ aj 24

D’allura, A., Molina, L. T., Zavala, M.,R., Flocke, Apel, A. E., G. Montzka, F., Campos, D. T.,Mexico Weinheimer, D., A. City Knapp, J., D. emissions Shetter, J., on and air3731–3743, Zheng, quality 2009. W.: Assessing and the chemistry, Atmospheric regional impacts Chemistry of and Physics, 9, Curci, G., Foret, G., Hodzic,quety, A., S., Mailler, Valari, S., M., Meleux, Vautard, F.,atmospheric R., Monge, composition and J.-L., modelling, Pison, Vivanco, Geosci. I., M. Model Siour, G.: G., Dev., CHIMERE 6, Tur- 2013: 981–1028, a 2013. modelthe cardiovascular for effects regional of air pollution, Future Cardiology, 8, 577–602,X., 2012. Yang, X. Q., Sun, J. N., Herrmann, E., Pet Coe, H.: Black carbon aerosolover the mixing United state, Kingdom, organic Atmospheric aerosols Chemistry and and aerosol Physics, optical 11, properties 9037–9052, 2011. of Environmental Chemistry, pp. 1–26, Springer-Verlag, Heidelberg, , 1998. biomass burning plumes on HONOPhysics, chemistry 15, in 1147–1159, eastern 2015. China, Atmospheric Chemistry and China through heterogeneous reactions andronment, changes 85, in 123–138, photolysis 2014. rates, Atmospheric Envi- its effect on aerosolResearch, 107, optical 4094, properties 2002. and direct radiative forcing,during Journal MCMA-2006/MILAGRO of campaign, Geophysical Atmospheric5182, Chemistry 2011b. and Physics, 11, 5169– H., Hu, B., Tanimoto, H.,photolysis and frequencies Akimoto, H.: and Impacts photochemistry ofronment, over aerosols 45, Central 1817–1829, on Eastern 2011a. summertime China, tropospheric Atmospheric Envi-

Menut, L., Bessagnet, B., Khvorostyanov, D., Beekmann, M., Blond, N., Colette, A., Coll,Miller, I., M. R., Shaw, C. A., and Langrish,Nie, J. W., P.: Ding, From A. particles J., to Xie, patients: Y. N., oxidative Xu, stress Z., and Mao, H., Kerminen, V. M., Zheng, L. F., Qi, X. M., Huang, Mena-Carrasco, M., R.Carmichael, G., Campbell, J. E., Zimmerman, D., Tang, Y., Adhikary, B., McMeeking, G. R., Morgan, W. T., Flynn, M., Highwood, E. J., Turnbull, K., Haywood, J., and Madronich, S. and Flocke, S.: The role of solar radiation in atmospheric chemistry, Handbook Lou, S., Liao, H., and Zhu, B.: Impacts of aerosols on surface-layer ozone concentrations in Li, G., Bei, N., Tie, X., and Molina, L. T.: Aerosol effects onLi, the J., photochemistry Wang, in Z., Mexico City Wang, X., Yamaji, K., Takigawa, M., Kanaya, Y., Pochanart, P., Liu, Y., Irie, Lesins, G., Chylek, P., and Lohmann, U.: A study of internal and external mixing scenarios and

5 20 25 30

15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 25

´ ´ ´ ´

e, J. C., Bessagnet, B., Mallet, M., Waquet, F., Chiapello, I., Minvielle, F., Pont, V., and e, J. C., Mallet, M., Pont, V., and Bessagnet, B.: Impact of the aerosol direct radiative forcing e, J. C., Mallet, M., Pont, V., and Bessagnet, B.: Evaluation of an aerosol optical scheme in e, J. C., Mallet, M., Bessagnet, B., and Pont, V.: Evidence of the aerosol core-shell mixing (2nd Edition), Wiley-Interscience publication, 2006. Menut, L.: Direct radiativeand effect atmospheric of dynamics the Russian during1999–2013, 2014. wildfires August and 2010, its Atmospheric impact Chemistry on and air Physics, temperature Kasper-Giebl, 14, A.: Physicochemicalwildfires: characterization Extreme event of of August 20102014. smoke in Moscow, aerosol Atmospheric Environment, during 96, 405–414, large-scale gaseous species and aerosols, Atmospheric Chemistry and Physics, 11,Presto, 1711–1727, A. 2011. A., Dubey, M. K.,of Yokelson, R. J., organics Donahue, N. in M., aerosols andGeoscience, Robinson, 7, from A. 647–650, L.: biomass 2014. Brownness burning linked to theirclimate black change, carbon Wiley-Interscience publication, content, 1998. Nature (ADRF) on the radiativeheatwave budget, of summer surface 2003 heat over fluxes WesternResearch, Europe. and 116, A d23119, atmospheric modelling doi:10.1029/2011JD016240, study., dynamics 2011. Journal during of Geophysical the the chemistry-transport model CHIMERE, Atmospheric Environment, 44, 3688–3699, 2010. state over Europe duringand AERONET the inversions, heat Geophysical Research wave2009. Letters, of 36, summer doi:10.1029/2009GL037334, 2003 by using CHIMERE simulations J. R., and Madronich, S.:near Effect Mexico of aerosols City andChemistry during NO2 and concentration MILAGRO: Physics, on 13, measurements ultraviolet 1011–1022, actinic and 2013. flux model calculations, Atmospheric

´ ´ ´ ´ er er er er

Seinfeld, J. H. and Pandis, S. N.: Atmospheric Chemistry and Physics. From air pollution to Popovicheva, O., Kistler, M., Kireeva, E., Persiantseva, N., Timofeev, M., Kopeikin, V., and Real, E. and Sartelet, K.:Saleh, Modeling R., of Robinson, E. photolysis S., rates Tkacik, D. over S., Europe: Ahern, impact A. T., on Liu, chemical S., Aiken,Seinfeld, A. J. C., H. Sullivan, and R. Pandis, C., S. N.: Atmospheric Chemistry and Physics. From air pollution to P P P

P Palancar, G. G., Lefer, B. L., Hall, S. R., Shaw, W. J., Corr, C. A., Herndon, S. C., Slusser,

5 20 25 30

15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ¨ utz, L., and Weinbruch, 26 ¨ om, R.: Evaluation of a sectional representation of size dis-

Kuznetsova, I. N., and Lapchenko,third V. quarter A.: of Ozone 2010, content Russian over Meteorology the and Russian Hydrology, 35, Federation 785–789, in 2010. the spectrometer connected with an4271, 2011. integrating sphere, Atmospheric Environment, 45, 4263– tributions for calculating aerosol19 optical 277–19 283, properties, 1996. Journal of Geophysical Research, 101, rithms, Radio Science, 26, 1393–1401, 1991. L.: Composition and mixing(Germany), state Atmospheric of Environment, 41, the 6102–6115, urban 2007. background aerosol intions the and impacts Rhein-Main on area ozone levels:2010. a study in a south China city, Environ. Chem., 7, 359–369, and Terra observations of the11, 2010 9287–9301, 2011. Russian wildfires, Atmospheric Chemistry and Physics, surrogate compounds: assessment oftion volatilisation on products the and reactive the uptake kinetics, role Phys. of Chem. OH Chem. concentra- Phys.,Interdisciplinary 15, Guide 5898–5915, to 2013. Fire Science, Wiley Blackwell, 2013. tem for the ozone concentrations2461, over 2001. the Paris area, Atmospheric Environment, 14, 2449– sources to particulate matterapproach, concentrations Atmospheric in Environment, Europe: 39, Testing hypotheses 3291–3303, with 2005. a modeling

Zvyagintsev, A. M., Ivanova, N. S., Blyum, O. B., Kotel’nikov, S. N., Kruchenitskii, G. M., Zhong, M. and Jang, M.: Light absorption coefficient measurement of SOA using a UV–Visible Wu, Z. P. and Wang, Y. P.: Electromagnetic scattering for multilayered spheres: Recursive algo- Wu, X., Seigneur, C., and Bergstr Wai, K. M. and Tanner, P. A.: Variations of aerosol properties due toWitte, regional J. source C., Douglass, contribu- A. R., da Silva, A., Torres, O., Levy, R., and Duncan, B. N.: NASA A-Train Turquety, S.: The Atmospheric Impact of Wildfires. Fire Phenomena andVautard, the R., Earth Beekmann, System: M., An Roux, J., and Gombert, D.: Validation of a hybridVautard, forecasting R., sys- Bessagnet, B., Chin, M., and Menut, L.:Vester, On B. the P., Ebert, contribution M., of Barnert, natural E. B., aeolian Schneider, J., Kandler, K., Sch Slade, J. H. and Knopf, D. A.: Heterogeneous OH oxidation of biomass burning organic aerosol

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27 Geographic distribution of the AOT between 5 and 12 August 2010 modelled by

tions of the two CALIOP profiles used on figure 8 wind is also indicated. M is the localization of Moscow and CFire and CnoFire are the localiza- Fig. 1a. Imaging Spectroradiometer) satellite sensor at 550 nm (right panel). The simulated 850 hPa CHIMERE at 500 nm (left panel) and measured by the Terra MODIS (Moderate Resolution Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper |

28 Continuation of Figure 1 Fig. 1b. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper |

29 Temporal evolution of the daily mean AOT over Moscow modelled by CHIMERE (at 400 Fig. 2. nm) and measured by AERONET (at 440 nm) between 5 and 12 August 2010 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 30

] due to the presence of aerosols. 2 Geographic distribution of the modelled daytime average percentage changes in the Fig. 3a. near-surface J[NO Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper |

31 Continuation of Figure 3. Fig. 3b. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 32

] due to the presence of aerosols. 3 Geographic distribution of the modelled daytime average percentage changes in the Fig. 4a. near-surface J[O Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper |

33 Continuation of Figure 4. Fig. 4b. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 34 (right) for the 8 August 2010, due to the presence of aerosols. 3 (left) and O 2

Geographic distribution of the daytime average percentage changes in the near-surface

concentration of NO Fig. 5. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 35

Daytime average percentage changes in the photolysis frequencies and concentrations

of nitrogen dioxide and ozone over Moscow as a function of modelled AOT (440 nm). Fig. 6. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper |

36 Mean VOC(ppmC) to NOx(ppm) ratio simulated over Moscow during the studied period Fig. 7. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 37 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | E, o N) and outside (noFire case, 33.3 o ) modelled by CHIMERE and measured by 1 E, 59.9 − o 38

The aerosol extinction coefficient (in km N) the intense aerosol plume (dotted lines correspond to the uncertainties on CALIOP o

aerosol plume is also indicated in red dashed line. of the daytime average percentage changes in the ozone concentration due to this intense measurements). The localisation of these two points is indicated on figure 1. The vertical profile Fig. 8. CALIOP for the 9 August inside52.0 (Fire case, 37.6 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 39 ) modelled with and without aerosol feedback along with corresponding 3 g/m µ

Temporal evolution (between 5 and 12 August 2010) of the near-surface ozone con-

observations at the Moscow monitoring station. Fig. 9. centration (in Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 40

a) Daytime average percentage reduction of the near-surface concentration of sul-

August Fig. 10. Repartition of this sulphate and SOA mass reduction between the 8 aerosol size bins for the 8 phates, secondary organic aerosols and PM10 over Moscow due to the aerosol feedback. b) Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | sim- ) 3 3 g/m µ and O 2 3 )( O 3 g/m µ )( 3 g/m 129134 66 66 0.46 0.42 82 88 Mod. Obs. Corr. RMSE µ ( ) 3 41 g/m µ 2 )( 3 NO g/m µ )( 3 1413 70 70 0.22 0.21 66 67 g/m Mod. Obs. Corr. RMSE µ (

statistical comparisons between the near-surface concentrations of NO

with without

are the temporal correlation and the root mean square error. Mod. and Obs. are the period-averaged modelled and observed concentration. Corr. and RMSE ulated with and without aerosols and measured at Moscow by an air quality station. Table 1. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ) 3 g/m µ 3 )( O 3 g/m µ )( 3 g/m 180185 161 161 0.19 0.16 48 54 Mod. Obs. Corr. RMSE µ ( ) 3 42 g/m µ 2 )( 3 NO g/m µ )( 3 31 90 0.60 67 32 90 0.60 66 g/m Mod. Obs. Corr. RMSE µ (

Same as in Table 1 but for daily maximum values

with without Table 2. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ) 3 g/m µ − 2 4 )( 3 SO g/m µ )( 3 g/m 2.242.33 0.48 0.48 0.23 0.45 1.80 1.88 Mod. Obs. Corr. RMSE µ ( ) 3 g/m µ − 3 )( 3 NO g/m µ 43 )( 3 g/m 0.140.19 0.12 0.12 0.20 0.26 0.15 0.23 Mod. Obs. Corr. RMSE µ ( ) 3 g/m µ E. o + 4 )( NH 3 g/m µ )( 3 g/m 1.091.16 0.86 0.86 0.48 0.42 1.03 1.04 Mod. Obs. Corr. RMSE Same as in Table 1 but for the near-surface concentrations of ammonium, nitrates µ (

with without

located at 54.9 N and 37.8 Table 3. and sulphates. Measurements come from the Danki EMEP station RU0018R (near Moscow)