Attribution and evolution of ozone from Asian wild fires using Attribution and evolution of ozone from Asian wild fires using satellite and aircraft measurements during the ARCTAS campaign satellite and aircraft measurements during the ARCTAS campaign

. We use ozone and carbon monoxide measurements from the Tropospheric Emission Spectrometer (TES), model estimates of Ozone, CO, and ozone pre-cursors from the Real-time Air Quality Modeling System (RAQMS), and data from the NASA DC8 aircraft to characterize the source and dynamical evolution of ozone and CO in Asian wildﬁre plumes during the spring ARCTAS campaign 2008. On the 19 April, NASA DC8 O 3 and aerosol

Aircraft and ground-based measurements have shown that Asian fires can influence O 3 concentrations over North America (Jaffe et al., 2004;Morris et al., 2006), the Arctic (Warnecke et al., 2008) and even Europe (Simmonds et al., 2005).For example, Bertschi and Jaffe (2005) have shown that Siberian fires have caused three ozone pollution events over the coast of Washington state in 2002.However, the impact of fires on tropospheric O 3 concentrations is challenging to estimate.Indeed, O 3 production is highly variable inside boreal fire plumes because of the influence of clouds and aerosols on photochemical production as well as highly variable PAN and NO x concentrations and the cycling between these species (Mauzerall et al., 1996;Lapina et al., 2006;Val Martin et al., 2006;Real et al., 2007;Verma et al., 2009).
During spring 2008, fires burned throughout Asia and Siberia.Smoke from these fires was observed across the Pacific by satellite and aircraft measurements during the ARCTAS/ARCPAC campaign.In this paper we use fire counts from the MODIS satellite instrument, CO and O 3 profiles from Tropospheric Emission Spectrometer (TES), insitu measurements from ARCTAS aircraft data and the Realtime Air Quality Modeling System (RAQMS) to characterize the factors influencing O 3 production and transport from these Asian fires.

Spring ARCTAS 2008
The NASA ARCTAS field campaign consisted of two phases; a spring and summer deployment and was part of the international IPY/POLARCAT arctic field program for atmospheric composition (http://www.polarcat.no/),which involved a consortium of countries several aircraft, surface, and shipbased measurement platforms.
The Spring phase of the ARCTAS campaign took place as a 3-week aircraft deployment in April 2008.It involved the NASA DC8 as an airborne platform for detailed atmospheric composition and two smaller aircraft to focus more closely on aerosols and radiation.As a complement to aircraft measurements, NASA's polarorbiting satellites (e.g.Terra, Aura, and the Atrain) observe the longrange transport of pollution and its seasonal accumulation in the Arctic, enabling a better understanding of pollution sources, transport pathways, and radiative impacts of boreal smoke plumes.
ARCTAS has four major scientific themes, including the impact of Boreal forest fires on atmospheric composition, and long-range transport of pollution to the Arctic including tropospheric ozone.As an atmospheric receptor of longrange transport of pollutants from the northern midlatitudes continents (Shaw, 1995;Quinn et al., 2007), the Arctic is increasingly beset by emissions from massive forest fires in boreal Eurasia (Hao and Ward, 1993;Cahoon et al., 1994;Tanimoto at al., 2000;Fromm et al., 2000;Dlugokenchy et al., 2001;Conard et al., 2002;Kasischke and Bruhwiler, 2003).However, there remain large uncertainties regarding the transport pathways and the relative contributions of different source regions to Arctic pollution (Staudt et al., 2001;Heald et al., 2003a;Liu et al., 2003;Liang et al., 2004;Koch and Hansen, 2005;Stohl, 2006;Shindell et al., 2008;Turquety et al., 2008;Shindell et al., 2008;Yashiro et al., 2009;Fisher et al., 2010;Jacob et al., 2010).Integration of satellite and aircraft observations with models through ARCTAS provides a means to address this issue (Eckhardt et al., 2003;Klonecki et al., 2003;Koch and Hansen, 2005;Stohl, 2006;Shindell et al., 2008).Spacebased observations of CO and ozone from the Tropospheric Emission Spectrometer (TES) are of particular interest for characterizing synoptic transport events, the seasonal buildup of pollution during winter and spring and ventilation of the Arctic to midlatitudes in spring and summer.
Another major focus of ARCTAS is to evaluate chemical transport model (CTM) simulations of sourcereceptor relationships for pollutants in the Arctic which is a challenge because of the complexity of the transport patterns involved, the paucity of meteorological data, the stratification of the atmosphere, and uncertain chemistry and surface interactions.

Overview of TES
TES is an infrared Fourier transform spectrometer that measures the thermal emission of the Earth's surface and atmosphere over the spectral range 650-2250 cm −1 .It was designed to provide simultaneous vertical profile retrievals of tropospheric O 3 , CO and other trace gases on a global basis (Beer et al., 2001;Beer, 2006).The nadir footprint is 5.3 km across the spacecraft ground track and 8.5 km along track for the 16-detector average (Beer et al., 2001).TES has two basic science operating modes: Global Survey and Special Observations.Global Surveys are conducted every other day while special observations are taken as needed in between Global Surveys.We used global survey observations of TES O 3 and CO obtained between 7 April and 19 April 2008 with a nadir sampling of 1.6 degrees spacing along the ground track.
The analysis presented here utilizes TES version 003 data (Osterman, 2007).An overview of the TES retrieval algorithm and error estimation are discussed by Bowman et al. (2006) and the characterization of errors and vertical information for individual TES profiles are discussed by Worden et al. (2004) and Kulawik et al. (2006).The vertical resolution of TES nadir O 3 retrievals is about 6 km for cloud-free scenes, with sensitivity to both the lower and upper troposphere (Worden et al., 2004;Bowman et al., 2006).To date, TES tropospheric O 3 validation has been conducted through comparisons with ozonesondes (Worden et al., 2007) and lidar (Richards et al., 2008).These validation studies show that TES O 3 estimates are typically biased high in the upper troposphere by approximately 10 %.Nassar et al. (2008) shows that TES O 3 is biased high by 3-10 ppb in the upper troposphere.For the springtime ARCTAS measurements, TES CO estimates typically have 1 degree of freedom for signal, when averaged over the free troposphere, and have uncertainties of 10-20 % (e.g.Worden et al., 2004;Zhang et al., 2006) (Luo et al., 2007).The agreement between TES CO profiles and in situ data is typically within 15 % and Lopez et al. (2008) reported that, in the 700-200 hPa pressure range where TES is the most sensitive to CO, in-situ measurements from the WB-57 aircraft agree with TES to within 5-10 %.Global comparisons between MOPITT (Measurement of Pollution in The Troposphere) and TES CO measurements have been performed as well (Ho et al., 2009) and show that for pressure layers where both instruments are most sensitive, the retrievals agree to within 10 %.In the same way, comparison between TES CO data in the upper troposphere and those from the ACE instrument show an agreement of 7.4 % at 316 hPa.

Real-time air quality modeling system: overview
Chemical and aerosol analyses from the Real-Time Air Quality modeling System (RAQMS) and ensemble wild fire trajectories are used to examine the different processes influencing the evolution of trace gases (e.g.O 3 and CO) within fire plumes prior to sampling these plumes by the DC8.RAQMS is a unified (stratosphere/troposphere), online (meteorological, chemical, and aerosol) modeling system which has been developed for assimilating satellite observations of atmospheric chemical composition and providing real-time predictions of trace gas and aerosol distributions (Pierce et al., 2003(Pierce et al., , 2007;;Kittaka et al., 2004).The chemical formulation follows a family approach with partitioning on the basis of photochemical equilibrium approximations.The non-methane hydrocarbon (NMHC) chemical scheme is based on the carbon bond lumped structure approach (Pierce et al., 2007).Photolytic rates are calculated using the FAST-JX code, an updated version of FAST-J2 code (Bian et al., 2003).The RAQMS aerosol model incorporates online aerosol modules from GOCART (Chin et al., 2002(Chin et al., , 2003)).Seven aerosol species (SO 4 , hydrophobic and hydrophilic organic carbon (OC), and black carbon (BC), dust, sea-salt) are transported.Biomass burning emissions in the RAQMS model includes daily, ecosystem and severity based estimates based on Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua fire detections (Al-Saadi et al., 2008).Fire emissions are a function of the fire severity and are injected over the depth of the planetary boundary layer for all fires except severe boreal fires, in which case the fire emissions are injected to 1km above the planetary boundary layer.Fire severity is estimated using the Haines index (Haines, 1988) developed by the US Forest Service.Emissions of other species are determined by combining published emission ratios for different ecosystems (Cofer et al., 1991;Andreae and Merlet, 2001).
The RAQMS chemical analysis used in the current study is from a retrospective 4-month (February-May 2008) 2 × 2 • assimilation that includes assimilation of cloud cleared OMI total column O 3 measurements and stratospheric O 3 profiles from the Microwave Limb Sounder (MLS) on the NASA Aura satellite.MODIS Aerosol Optical Depth (AOD) from instruments onboard the Terra and Aqua satellites (Remer et al., 2005;Davies et al., 2004) was also assimilated.A Mie code based look-up table of speciated aerosol mass extinction coefficients and relative humidity dependent hygroscopic growth factors is used to convert the predicted aerosol mass to speciated extinction, which is integrated vertically to obtain a first guess AOD for assimilation.The masses of all aerosol species are adjusted within each model layer on the basis of the total AOD analysis increment and the relative contribution of each aerosol species to the total layer extinction.The resulting RAQMS aerosol analysis is in good agreement with April 2008 global Aeronet measurements (r = 0.7, bias = 0.05).During the chemical and aerosol assimilation cycle the RAQMS meteorological forecasts are reinitialized from NOAA Global Forecasting System (GFS) analyses at 6 h intervals.
We have also conducted a series of RAQMS simulations to identify signatures from the Asian wild fires.The first simulation, which did not include ozone or aerosol assimilation but included all Asian wildfire emissions, is referred to as the "baseline" simulation.We then conducted a series of RAQMS simulations where we restricted April 2008 wildfire emissions to within the Kazakhstan, Siberian, or Thailand regions.These simulations did not include MODIS aerosol or OMI ozone assimilation so that we could assess differences in tropospheric ozone that arise due to the wildfires.These simulations included assimilation of MLS ozone profiles above 50mb so that stratospheric ozone was constrained for reliable estimates of the effects of stratospheric/tropospheric exchange processes.Differences between the baseline RAQMS simulation and simulations with the restricted wildfire emissions are then used to infer which fires were primarily responsible for the aerosol and tropospheric ozone enhancements observed by the DC8.
We use RAQMS chemical and aerosol analyses in conjunction with ensemble trajectory analysis (Pierce et al., 2009;Verma et al., 2009) to follow the chemical evolution of ensemble trajectories initialized at daily wildfire locations.The resulting Lagrangian photochemical histories of the wildfire plumes can be used to relate emissions from these biomass burning regions to the trace gas concentrations and location of the plumes measured by the DC8.Two plumes are examined, one plume originating from Kazakhstan and one originating from Thailand.The DC8 made in situ measurements of the Kazakhstan plume as indicated by the RAQMS trajectory analysis (Fig. 3a).This trajectory analysis indicates that the plume originates from Kazakhstan on the 7 April.After initialization, ensemble trajectories are transported eastward, in the middle troposphere, over North Asia, across the Pacific via the Bering Sea and then south of   Alaska where they are intersected by the NASA/DC8 flight track on the 19 April 2008, 12.5 days after initialization.The start day was marked by a sudden increase of Kazakhstan fire CO emissions from less than 0.5 to more than 1.5 TgC day −1 .During transport over Asia, the RAQMS model indicates that the wildfire plume was enhanced by Siberian biomass burning emissions with increase in CO and, carbonaceous aerosol (BCOC) (not shown in the figures).Moreover, the plume subsequently mixed with anthropogenic emissions over the Bering Sea, as indicated by increased SO 4 concentrations in RAQMS that is consistent with aircraft SO 2 measurement of approximately 450 pptv (Fig. 7e).
Another plume identified by RAQMS forward wildfire trajectory analysis (Fig. 3b) and measured by aircraft lidar (Fig. 4) originates from Thailand on 9 April.This date matches with high Thailand fire CO emissions up to 3.0 TgC day −1 , an intensity two times higher than the Kazakhstan fire.Several studies (Bey et al., 2001;Jacob et al., 2003) have already shown that CO from biomass burning in Southeast Asia is transported over the Pacific by the particularly strong Asian outflow in spring.The frequent cyclogenesis off the coast of East Asia transport pollution to the free troposphere (Stohl, 2001;Liu et al., 2003;Miyazaki et al., 2003) where air masses are isolated from the surface.Then, plumes are transported to northern high latitudes and divided into northern and southern branches.The plume that originated from Thailand was transported over China and the RAQMS model suggested no enhancement by anthropogenic emissions.The ASR is defined as the ratio of the attenuated aerosol backscatter laser light to the calculated molecular backscatter expected from an aerosol free atmosphere (Browell, 2001).
Values of ASR (591 nm) ranging from 0.1 to 5.0 and showing high concentrations of aerosols were observed in the lower and middle troposphere (2 to 6 km) all along the flight track.Forward model trajectories from the wildfire locations (Sect.2.3.1)indicate that this plume originated primarily from the Kazakhstan and Baikal fires with contributions from anthropogenic emissions.In the same way, aerosols were detected in the upper troposphere (8 to 12 km) between 45 and 55 degrees of latitude North.Forward model trajectories from the wildfire locations (Sect.2.3.1)indicate that this plume came from the Thailand fires.Both middle and upper tropospheric plumes showed enhanced ozone concentrations relative to the background as seen in Fig. 5.In the same figure, O 3 concentrations higher than 125 ppbv are observed in the upper troposphere around 56 degrees of latitude north (20:00 UTC time).This is the result of a stratospheric air mass descent and is not due to wildfires.

In situ measurements of plume chemical composition
The NASA DC8 aircraft flew through two parts of the lowermiddle tropospheric fire plume between 55 • N and 50 • N (20:10 to 21:10 UTC) and around 40 • N (around 23:00 UTC).Unfortunately, no in situ sampling of the high altitude tropospheric plume was performed.Figure 6 shows O 3 , CO, BC, NO x , SO 2 and PAN concentrations along the DC8 flight track as a function of UTC time (from top left to bottom right panel).Each graph is color coded with HCN concentrations, a well-known fire tracer, and compared to RAQMS reanalysis at same location.As shown by the HCN color coding with HCN higher than 1500 pptv (green to red colors), the lower/middle tropospheric biomass burning plume which originated from Kazakhstan, was sampled twice between 20:10 and 21:10 UTC, and around 23:00 UTC.Both periods show high CO, SO 2 , BC and PAN levels.The high levels of CO (Roths and Harris, 1996;Jaffe et al., 1997, Yurganov et al., 1998;Ponchanart et al., 2003;Fisher et al., 2010) and aerosols (Haywood and Boucher, 2000;Zhao et al., 2002;Eck et al., 2003;Myhre et al., 2003;Massie e al., 2004, Abel et al., 2005;Reid et al., 2005a, b;Forster et al      2007) along with high levels of HCN observed by in situ data validate the biomass burning origin of the plumes.Moreover, SO 2 measurements are significantly above background levels in both part of the lower/middle tropospheric plume; these enhanced amounts suggest mixing of the biomass burning plume with anthropogenic pollution.
The top left panel of Fig. 6 shows O 3 concentrations as high as 100 ppbv in the northern part and 85 ppbv in the southern part of the plume.These high ozone concentrations are co-located with significant concentrations of PAN and NO x .PAN is an important source of NO x and NO x is an important pre-cursor of ozone indicating that ozone production can be sustained along the plume if there is a sufficient PAN reservoir and the plume moves to higher temperatures (Mauzerall et al., 1998;Real et al., 2007).
Comparisons between the RAQMS analysis (black lines in Fig. 6) and in situ measurements from the DC8 on 19 April show that the elevated CO, BC, NO x , SO 2 , and PAN due to biomass burning (high HCN) observed by the aircraft is underestimated in the northern part of the plume.As seen in the top panel of Fig. 7 the RAQMS model estimates of black carbon are not at the same altitude or have the same width as the elevated plume found at 4km in the DIAL aerosol scattering ratio and sampled by the DC8 at this time.Instead, RAQMS shows a broader plume that is at a lower altitude.This broader plume was sampled again at its southern location, where RAQMS shows somewhat better agreement with the in situ measurements but is still low.These underestimates are a consequence of diffusive transport associated with the relatively coarse horizontal (2 × 2 degrees) and vertical (0.5-1 km in the free troposphere) resolution of the RAQMS model.RAQMS shows no NO x enhancements in the northern part of the plume and consequently underestimates ozone production.
In summary, the aircraft data suggest that the observed plumes in the middle and lower troposphere originate from biomass burning and were subsequently mixed with anthropogenic pollution.However, RAQMS is not able to capture the plume pollutant concentrations with accuracy due to its coarse resolution.The lidar data also indicate a plume of ozone in the upper troposphere that is due to both biomass burning but potentially with a contribution from stratospheric/tropospheric exchange.We next use the aircraft data along with the forward wildfire trajectories (Sect.2.3.1.)and CO and ozone profile measurements from TES as well as the RAQMS model to confirm the biomass burning origin of these plumes and explain the ozone distributions observed by the aircraft on 19 April 2008.

Source identification of observed plumes
As discussed earlier, significant wild fires occurred in western Asia (Kazakhstan), eastern Asia (Siberia) and southeastern Asia (Thailand).Satellite fire counts over Russia were more than two times the April average in April 2008 (Fisher et al., 2010).Kazakhstan and Siberian fires are mainly due to burning of mixed coniferous and deciduous forest and croplands as observed by one-degree land cover derived from AVHRR.Thailand fires are due to burning of broadleaf evergreen forest, grassland and cropland (http://glcf.umd.edu/data/landcover/).

Ozone origin in Asian fire plumes
Using TES and RAQMS CO and O 3 profiles we observe and interpret CO and O 3 concentrations during transport of the Kazakhstan/Siberian and the Thailand plumes from emission to flight location.We also discuss the impact of fire emissions and stratospheric-tropospheric exchange on O 3 concentrations.

Kazakhstan and Siberian fires
We first examine the Kazakhstan plume CO and O 3 concentrations at different locations during transport across the  Tropospheric concentrations of CO are plotted against ozone using estimated concentrations from the TES profiles over the Kazakhstan fire in the top left panel of Fig. 8a.Tropospheric CO and ozone concentrations from RAQMS chemical analysis are plotted in the bottom right panel of Fig. 8a.Although the TES estimates of any individual pressure level in any profile is dependent on the a priori used to regularize the TES profile retrievals, applying the instrument operator (which is dependent on the a priori constraint and the averaging kernel, or retrieval sensitivity to true state) to the model will remove the effect of the a priori and sensitivity in the comparison; the comparison will then show if the model is overestimating the variability of ozone or CO and/or whether the correlation between ozone and CO in the  data is consistent with the model (e.g.Zhang et al., 2006).If the ozone/CO variability from the model is consistent with the TES estimate after having applied the instrument operator then our conclusion would be that the model estimate of the ozone/CO variability and correlation is reasonable within the TES errors.
The bottom left panel shows these same RAQMS concentrations after the TES averaging kernel and constraint vector have been applied to account for the TES vertical sensitivity and retrieval bias (e.g.Jones et al., 2003;Pierce et al. 2009;Worden et al., 2004;Bowman et al., 2002Bowman et al., , 2006Bowman et al., , 2009) ) which will be referred to as the "adjusted" RAQMS model.The CO/O 3 scatter plots are color-coded by the predicted CO enhancement associated with the Kazakhstan wildfires, as determined by the differences between the RAQMS baseline and no Kazakhstan wildfire emission simulations.Colorcoding helps to indicate the impact of Kazakhstan fire emissions on RAQMS and TES CO and O 3 .In all graphs, green to   The initial comparison between TES and adjusted RAQMS (left side of Fig. 8a) shows good agreement in maximum CO (which is associated with the wildfire plume) but RAQMS shows larger minimum CO (160 ppbv vs. 110 ppbv).This is due to overestimates in RAQMS back- ground CO mixing ratios that increase with latitude in the Northern Hemisphere (also evident in the comparison with in situ measurements on 19 April (Fig. 6b).RAQMS ozone initially (7 April) ranges from 45-65 ppbv which is in agreement with TES except for a few points with O 3 between 70 and 90 ppbv (also evident on 14 April, Fig. 8b).These retrieved ozone enhancements are found in the upper troposphere in the TES retrieval and not associated with the Kazakhstan wildfire plume and indicate underestimates in stratospheric-tropospheric exchange in RAQMS relative to the TES retrievals.As shown by RAQMS, the magnitude of the wildfire CO enhancement for this plume could be as high as 600-700 ppbv on 7 April (see lower right in Fig. 8a).The negative correlation between O 3 and CO suggests that the majority of the sampled air may have originated from the stratosphere.Therefore, for TES observations over Kazakhstan source region (Fig. 8a), elevated O 3 is mainly due to stratospheric enhancements and wildfire emissions are not observed to significantly contribute to O 3 enhancements within the plume.This can be due to the fact that the plume sampling occurs right after plume emission and does not allow a sufficient time for O 3 precursors to react in the troposphere and produce O 3 .
After emission, the Kazakhstan wildfire plume was transported eastward in the middle troposphere (∼500 hPa) over Asia.Before reaching the Pacific, the plume encountered fire emissions from Siberia (Baikal) (Fig. 8b) leading to additional CO enhancements (up to 600 ppbv) that were not associated with the initial Kazakhstan emissions (bottom right panel of Fig. 8b).TES and the adjusted RAQMS model agree in the estimation of maximum CO concentration (respectively 220 ppbv and 250 ppbv) that are associated with the wildfire emissions.However, the adjusted RAQMS model shows higher background CO concentrations than TES by more than 70ppbv.The adjusted RAQMS model underestimates maximum O 3 concentrations observed by TES by more than 50 ppbv due to errors in representation of stratospheric/tropospheric exchange in the RAQMS model due to the relatively coarse horizontal and vertical resolution.
As suggested by the aircraft in situ SO 2 measurements (Sect.2.2.2) and confirmed by the RAQMS analysis of the Lagrangian chemical evolution of the Kazakhstan wildfire plume (not shown here), the plume mixed with Asian anthropogenic emissions.The plume was then transported in the middle troposphere over the Pacific via the Bering Sea and reached flight location around 18 April (Fig. 8c).Both TES and the adjusted RAQMS model show similar maximum CO concentrations (around 225 ppbv) and O 3 concentrations (max O 3 = 60 ppbv, min O 3 = 40 ppbv).In contrast, in situ measurements within the wildfire plume from flight 11 give O 3 concentrations ranging from 80 to 100 ppbv in the plume (black dots in Fig. 9).Investigation of TES and MODIS cloud data show that there is high cloud density over the region where the DC8 sampled the main part of the plume.As a result, TES shows little sensitivity in O 3 between 50 and 60 • N. Background CO concentrations are still overestimated by the adjusted RAQMS model by more than 60 ppbv compared to TES CO (Fig. 8c), which is consistent with the comparisons with in situ CO in Fig. 9. Finally, TES shows a low O 3 event, down to 20 ppbv of O 3 , which is not captured by the adjusted RAQMS model (Fig. 8c). Figure 9 shows in situ measurements onboard the DC8 aircraft with higher concentrations of O 3 ranging from 60 to 120 ppbv collocated with CO over 150 ppbv (pink dots) and a positive O 3 /CO correlation showing O 3 production in the plume.In addition, the background air shows a negative correlation of low CO with high ozone indicated stratospheric influence.The RAQMS model estimates are consistent with the background ozone and CO showing stratospheric influence on the observed ozone but does not show a positive correlation of ozone and CO in the wildfire plume.We attribute this discrepancy to transport errors in the RAQMS model and the narrowness of the plume feature which result in difficulty in modeling the photochemical production of ozone within the plume.

Thailand fires
We next examine the Thailand plume CO and O 3 concentrations at different locations during transport from the source and across the Pacific where the Thailand plume was eventually observed by DIAL on the DC8.Table 2 shows  Figure 10 shows vertical profiles of ozone and CO concentrations downwind of the Thailand fires.Significant CO concentrations are observed near the surface between 10 and 25 degrees latitude with higher than average CO concentrations in the middle/upper troposphere.The averaging kernels (averaging kernels not shown but can be referenced

Discussion
The combination of TES and RAQMS wildfire sensitivity experiments and ensemble wildfire trajectories allows us to attribute observations of ozone and CO to their respective sources in Kazakhstan/Siberian and in Thailand as well as to examine the effects of convective lofting and stratospheric/tropospheric exchange on the observed ozone concentrations.We next use RAQMS sensitivity studies to quantify the impact of Asian biomass burning plumes on aerosols, O 3 and CO sampled by the DC8.For these studies the emissions from each fire are set to zero and the ozone and CO concentrations are then compared to the run in which the emissions are non-zero.Note that for these sensitivity studies we do not use the RAQMS simulation with assimilated column ozone from OMI because the OMI analysis increment (which affects the entire model profile) would influence the difference in ozone and CO between the run without emissions and the run with emissions.We did however, retain assimilation of MLS stratospheric profiles above 50 mb so that the influence of stratosphere/troposphere exchange processes on the wildfire plumes can be more accurately represented.We find that Kazakhstan wildfires account for the majority of lower tropospheric wildfire signatures with peak CC, CO and O 3 enhancements respectively of 3.4 ppbv, 33 ppbv and 5.5 ppbv (not shown).However, Siberian fires account for a small fraction of lower tropospheric wildfire signatures mostly below 2 km and at northern (60 • N) part of DC8 flight.As seen before in Sect.3.1.1,Kazakhstan fire trajecto-ries overpass Siberian fires and entrain emissions from those fires.As a result, impacts on CO, CC and O 3 by Siberian fires are collocated with Kazakhstan fires dCC, dCO and dO 3 .However, these estimates must be used with caution because the RAQMS model cannot capture the fine vertical extant of the Kazakhstan smoke plume nor the ozone production in the plume that is apparent from the aircraft in situ data; this points to the need for measurements over these sources regions and along the plume in order to better characterize our understanding of the emission, transport, and photochemistry of these fine-scale plumes.
Unlike the Kazakhstan and Siberian fires, the Thailand fires have a significant impact on CC, CO and O 3 profiles in the upper troposphere.They account for the entire upper tropospheric fire signatures along the DC8 flight path with peak CC, CO and O 3 enhancements of 2.2 ppbv, 66 ppbv and 9.5 ppbv respectively.The lower dCC/dCO ratios of the Thailand fires relative to the Kazakhstan fires is most likely due to stronger hydrophilic organic carbon and black carbon losses within the Thailand plumes due to convective transport into the upper troposphere.

Conclusions
Using satellite ozone and CO tropospheric profile estimates from TES, and in situ and lidar data from the ARCTAS campaign, we explored the impact of Siberian Boreal and Southeast Asian fires on tropospheric chemistry, long-range transport of associated pollutant over the Pacific, and the chemical and dynamical processes influencing ozone concentrations.
On 19 April 2008, Differential Absorption Lidar (DIAL) onboard of NASA/DC8 aircraft sampled two major biomass burning plumes ashore of western North America.Real time Air Quality Modeling System (RAQMS) ensemble wildfire trajectory analysis showed that those plumes originated from Kazakhstan and Thailand where large wildfires were taking place with monthly mean CO emissions three times higher than usual April means.In-situ measurements onboard the aircraft showed high concentrations of CO, PAN, and BC consistent with biomass burning along with signatures of anthropogenic emissions (SO 2 ) and significant O 3 enhancements (up to 100 ppbv).RAQMS sensitivity studies allowed us to assess the relative impact of Asian fires on CO, O 3 and CC concentrations along DIAL profiles.It showed that Thailand fires were responsible for almost the entire biomass burning signature in the upper troposphere (8 to 12 km); whereas Kazakhstan and Siberian fires were responsible for the majority of the fire signature in the lower middle troposphere (2 to 6 km).
We examined CO and O 3 concentrations within these two distinct plumes using TES and RAQMS data and characterized the evolution of the ozone and CO concentrations, and their correlations, along their respective transport pathways.Over the Kazakhstan fire source region, the model suggests that a significant component of the O 3 observed by TES was due to stratospheric enhancement.Upon transport eastward in the middle troposphere over Asia, the plume went over the Siberian fire and was exposed to additional CO and O 3 precursor enhancements as indicated by both the RAQMS model and the aircraft in situ data.Finally, the plume crossed the Pacific over the Bering Sea and reached the flight location on 19 April.Along the flight track, TES and RAQMS observe similar O 3 concentrations ranging from 40 to 60 ppbv.However, in situ measurements from flight 11 measured O 3 concentrations ranging from 80 to 100 ppbv in the plume; this increased ozone enhancement measured by aircraft could be due to localized ozone production within narrow filaments of the wildfire plume that are not observed by TES due to its relatively coarse vertical resolution and not captured by RAQMS due to it's relatively coarse vertical and horizontal resolution and due to transport errors.
The upper tropospheric plume observed by DIAL originated from Thailand in Southeast Asia.TES observations near the source indicate photochemical production of ozone in the plume along with uplift of the plume into the upper troposphere south of the Tibetan plateau, similar to the convective lofting affecting ozone during the summertime Asian monsoon (e.g.Liu et al., 2009;Worden et al., 2009).As indicated by the LIDAR data (Fig. 5), the TES data and the RAQMS model in Figs. 10 and 11, stratospheric air with high ozone and low CO concentrations likely mixed into the edges of the plume (e.g.Jourdain et al., 2009).Then, the plume was transported in the middle/upper troposphere (between 100-400 hPa) over the Pacific.Along the flight track, on 19 April, TES and the adjusted RAQMS model give O 3 concentrations ranging from 50 to almost 420 ppbv.These estimates of ozone and CO due to both the fires and stratospheric exchange are limited by the coarse (∼6 km) vertical resolution of TES and the transport and emissions uncertainties in the RAQMS model.However, this study represents one of the first times that observations of ozone were tracked from the source to aircraft using satellite data where they could be interpreted using the suite of measurements of ozone pre-cursors aboard the aircraft.The satellite data complement the aircraft data by observing the effects of stratospheric/tropospheric exchange on ozone concentrations and convective lofting on the smoke plumes prior to being measured by the aircraft.
Considering the seasonal trend of biomass burning pollutant transport from Asia, it is important to characterize these events in order to understand their impact on air quality and climate.Recently, increases in CO by biomass burning in boreal forests and Southeast Asian fire emissions have been identified as affecting human health (Maynard and Waller, 1999) and perturbing atmospheric chemistry at regional and even global scales (Logan et al., 1981;Roths and Harris, 1996;Novelli et al., 1998;Bowman et al., 2009;Jones et al., 2009).Increases in population in Southeast Asia tend to increase burning of postharvest agricultural waste that is an important type of biomass burning in this region of the world (Crutzen and Andreae, 1990;Nguyen et al., 1994).Increased temperatures from global warming also tend to increase drought and decrease snow cover in Northern Asia leading to increases in fuel quantity and a longer fire season (Euskirchen et al., 2007).
The plume was transported eastward over China and crosses the Pacific along 40 • N to reach NASA/DC8 flight track on 19 April 2008, 10 days after emission.
11, the DIfferential Absorption Lidar (DIAL) instrument measured elevated concentrations of O 3 and aerosols in what appeared to be two biomass burning plumes (Figs.4 and 5).
Figure 4 shows Aerosol Scattering Ratio (ASR) profiles measured by DIAL during DC8 flight 11 as a function of UTC time, latitude and longitude.

Figure 4 :
Figure 4: Aerosol Scattering Ratio (ASR) from the Differential Analysis Lidar during DC8 flight 11 and square limiting aerosol plumes

Figure 5 :
Figure 5: Differential Analysis Lidar ozone (O 3 ) mixing ratio.The rectangles indicate the two ozone plumes

Figure 7 :
Figure 7: RAQMS Black Carbon (BC) profile and comparison between RAQMS (dotted line) and in situ (solid line) BC concentrations during DC8 flight 11 Fig. 7. RAQMS Black Carbon (BC) profile and comparison between RAQMS (dotted line) and in situ (solid line) BC concentrations during DC8 flight 11.

Figure 8a :
Figure 8a: (top left) TES ozone and CO over Kazakhstan fires.(top right) TES measurement locations.(bottom right) RAQMS estimates of CO and ozone.(bottom left RAQMS estimates of CO and Ozone after applying TES a priori and averaging kernel to RAQMS estimates.

Fig. 8a .
Fig. 8a.(Top left) TES ozone and CO over Kazakhstan fires.(Top right) TES measurement locations.(bottom right) RAQMS estimates of CO and ozone.(Bottom left) RAQMS estimates of CO and Ozone after applying TES a priori and averaging kernel to RAQMS estimates.

Figure 8b :
Figure 8b: Same as in 8a but over Siberia

Figure 8c :
Figure 8c: Same as 8a and 8b but near the DC9 measurements
dates, locations and UTC time of each TES profiles used during the study.Three steps of the plume transport are discussed.First, we observe O 3 and CO concentrations in the plume immediately downwind of source region (Thailand) during convective lifting over the Tibetan plateau (11 April 2008).Then, we quantify plume evolution at an intermediate location over the Pacific (15 April 2008) showing strong stratospheric air masses influence.Finally, we examine plume O 3 and CO concentrations near the NASA/DC8 flight location (19 April 2008).

Fig. 10 .
Fig. 10.(Top panel) Observed TES ozone over Thailand and south of the Himalayas.(Bottom panel) Observed TES CO.

R.
Fig. 11a.Same as Fig. 8 but near source region for Thailand Fires.

Figure 11b :
Figure 11b: Same as Figure 11a but downwind of Thailand plume

Fig. 12 .Figure 13 :
Fig. 12. (Top panel) Estimated ozone due Thailand fires from RAQMS sensitivity runs (bottom panel) estimated CO due to Thailand fires.Right panel shows the orbit track.These figures should be compared to the observed ozone from TES in Fig. 10.

Figure 13
Figure 13 shows RAQMS Carbonaceous aerosol (CC), CO and O 3 enhancements relative to the baseline simulation due to Asian fire emissions (Kazakhstan, Siberia and Thailand combined) and RAQMS baseline CC along the DC8 flight 11 (from top left to bottom right).The RAQMS baseline CC distribution (bottom right panel) along the DC8 flight curtain agrees spatially with the DIAL measurements (Fig. 4) and shows a major carbon aerosol enhancement in the lower troposphere (2-6 km) (up to 4.6 ppbv) and lower aerosol amounts in the upper troposphere (8-12 km) (up to 2.4 ppbv).Comparison between the Asian wildfire and Baseline CC indicates that emissions from Kazakhstan, Baikal, and Thailand wildfires account for more than 90 % of carbonaceous aerosols in the upper and lower/middle troposphere.However, upper tropospheric CC enhancements (2.2 ppbv) are two times less than lower/middle tropospheric enhancements (4.2 ppbv).On the other hand, upper tropospheric CO (dCO = 72 ppbv) and O 3 (dO 3 = 11 ppbv) enhancements are larger than lower tropospheric enhancements (dCO = 50 ppbv and dO 3 = 8.5 ppbv).

Table 1 .
Dates, locations and UTC time of each TES profile used during the Kazakhstan/Siberian wildfire plume study.

Table 2 .
Dates, locations and UTC time of each TES profile used during the Thailand wildfire plume study.