Characterisation of African biomass burning plumes and impacts on the atmospheric composition over the South-West Indian Ocean

. We present an investigation of biomass burning (BB) plumes originating from Africa and Madagascar based on measurements of carbon monoxide (CO), ozone (O 3 ), nitrogen dioxide (NO 2 ) and a suite of volatile organic compounds (VOCs) obtained during the dry season of 2018 and 2019 at the high altitude Maïdo observatory (21.1 ◦ S, 55.4 ◦ E, 2250 m above sea level), located on the remote island of La Réunion in the South-West Indian Ocean (SWIO). Biomass burning plume episodes were identiﬁed from increased acetonitrile (CH 3 CN) mixing ratios. Enhancement ratios (EnRs) — relative 5 to CO — were calculated from in situ measurements for CH 3 CN, acetone (CH 3 COCH 3 ), formic acid (HCOOH), acetic acid (CH 3 COOH), benzene (C 6 H 6 ), methanol (CH 3 OH) and O 3 . We compared the EnRs to emission ratios (ERs) — relative to CO — reported in literature in order to estimate loss/production of these compounds during transport. For CH 3 CN and CH 3 COOH, the calculated EnRs are similar to the ERs. For C 6 H 6 and CH 3 OH, the EnR is lower than the ER, indicating a signiﬁcant net sinks of these compounds. For CH 3 COCH 3 and HCOOH, the calculated EnRs are larger than the ERs. The discrepancy 10 reaches an order of magnitude for HCOOH (18 – 34 pptv ppbv − 1 compared to 1.8 – 4.5 pptv ppbv − 1 ). This points to signiﬁcant secondary production of HCOOH during transport. The Copernicus Atmospheric Monitoring Service (CAMS) global model simulations reproduces well the temporal variation of CO mixing ratios at the observatory but underestimates O 3 and NO 2 mixing ratios in the plumes on average by 16 ppbv and 60 pptv respectively. This discrepancy between modelled and measured O 3 mixing ratios was attributed to i) large uncertainties in VOC and NO x (NO+NO 2 ) emissions due to BB in CAMS and ii) 15 misrepresentation of NO x recycling in the model during transport. Finally, transport of pyrogenically emitted CO is calculated with FLEXPART in order to i) determine the mean plume age during the intrusions at the observatory and ii) estimate the impact of BB on the pristine marine boundary layer (MBL). By multiplying the excess CO in the MBL with inferred EnRs at the observatory, we calculated the expected impact of BB on CH 3 CN, CH 3 COCH 3 , CH 3 OH and C 6 H 6 concentrations in the MBL. These excesses constitute increases of ∼ 20% – 150% compared to background measurements in the SWIO MBL 20 reported in literature.


Introduction
Non-methane volatile organic compounds (NMVOCs) are key tropospheric constituents. Many of them are highly reactive with the major atmospheric oxidants, especially with the OH radical, and therefore they strongly affect the oxidation capacity of the troposphere (Atkinson, 2000). By being a strong sink for OH, they also exert control on the lifetime of methane (Zhao et al.,25 2019) and thus on climate. Moreover, OH-initiated NMVOC oxidation modulates tropospheric O 3 concentrations and is the major source of this secondary pollutant in high NO x (NO+NO 2 ) environments . Less volatile NMVOC oxidation products contribute to the formation and growth of secondary organic aerosol which deteriorates air quality and affects radiative forcing, and hence climate, both in a direct (by interacting with solar radiation) and indirect way (by acting as cloud condensation nuclei) (IPCC, 2013). 30 Whereas atmospheric oxidation of precursor VOC species is the dominant source of many oxygenated VOCs (OVOCs), primary anthropogenic emissions and (bidirectional) exchange with the biosphere and the ocean and biomass and biofuel burning also contribute to the atmospheric OVOC burden (Mellouki et al., 2015). Photochemical degradation and dry and wet deposition are the major sink processes. Global OVOC budgets are still prone to large uncertainties due to an incomplete understanding of photochemical production and loss processes and ocean-atmosphere exchange (Millet et al., 2010;Fischer et al., 2012;Read 35 et al., 2012;Wang et al., 2019), and a paucity of (O)VOC data, especially at remote marine areas where the oxidative capacity of the atmosphere is mainly controlled by OVOCs (Lewis et al., 2005;Carpenter and Nightingale, 2015).
The South-West Indian Ocean (SWIO) is one of the few pristine regions on Earth. It is largely decoupled from emissions originating from large bodies of land and is well suited to characterise remote marine air composition and ocean emissions (Colomb et al., 2009;Mallet et al., 2018). Located in the SWIO is the French overseas department La Réunion, a small volcanic island, 40 home to the high altitude Maïdo atmospheric observatory (21.1 • S, 55.4 • E, 2250 m above sea level) ( Baray et al., 2013), hereafter referred to as RUN. From October 2017 to November 2019, a high-sensitivity quadrupole-based Proton Transfer Reaction Mass Spectrometry VOC analyser (hs-PTR-MS) was deployed at RUN in the framework of the OCTAVE (Oxygenated Compounds in the Tropical Atmosphere: Variability and Exchanges) project (http://octave.aeronomie.be). In combination with other ground-based and satellite data, the resulting near-continuous high time-resolution two-year data set will serve to better 45 constrain VOC emissions in the remote tropical marine atmosphere and to identify missing sources. Part of this dataset has already been used in a source apportionment study of formaldehyde (HCHO) (Rocco et al., 2020).
The present paper contributes to the disentanglement of the different sources contributing to the (O)VOC composition at RUN by focusing on the role of biomass burning (BB). It is established from ground-based remote-sensing Fourier Transform Infrared (FTIR) observations that BB impacts the atmosphere over La Réunion. The BB events affecting the region occur most 50 frequently in southern Africa and Madagascar but impacts from burning in South America and Malaysia has also been identified (Duflot et al., 2010;Vigouroux et al., 2012). Seasonality of in situ CO concentrations at RUN indicates that BB plumes also impact the atmospheric composition at the surface (Zhou et al., 2018). This was confirmed by the hs-PTR-MS dataset generated at RUN for the OCTAVE project (Fig. A1). Biomass burning represents the second largest global source of NMVOC emissions (Yokelson et al., 2008;Akagi et al., 2011). Pyrogenic emissions are reasonably well constrained by numerous lab-time. In addition, observations of BB plumes at RUN were used to evaluate the global near-real time (NRT) CO, O 3 and NO 2 modelled concentrations at RUN from the Copernicus Atmospheric Monitoring Service (CAMS). Finally, we propose a way to use in situ VOC measurements at RUN to estimate the impact of BB plumes on the pristine marine boundary layer (MBL) over the SWIO. This is done for CH 3 CN, CH 3 COCH 3 , C 6 H 6 and CH 3 OH.
In section 2 the instruments, methods and models used in this study are presented. The results are shown in section 3 and 70 discussed in section 4.  Duflot et al. (2019); Baray et al. (2013) and Zhou et al. (2018).
In the frame of the OCTAVE project, a hs-PTR-MS instrument (Ionicon Analytik GmbH, Austria) was deployed at RUN 80 from October 2017 to November 2019. This resulted in a near-continuous high time-resolution two-year data set of volatile organic compounds (VOCs). The instrument was run in the multiple ion detection mode using H 3 O + precursor ions with a total cycle time of ∼ 2.7 min. Regular calibrations of the hs-PTR-MS were performed by diluting a gravimetrically prepared VOC/N 2 mixture (Apel-Riemer Environmental Inc., Miami, FL, USA; stated accuracy of 5% for all VOCs) with zero-VOC air obtained by sending ambient air through a catalytic converter (Parker, type HPZA-3500, Haverhill, MA, USA). This resulted 85 in VOC concentrations in the lower ppbv range. Calibrations as a function of relative humidity were performed bimonthly by controlling the humidity of the zero air with a dew point generator (LI-COR LI610, Lincoln, Nebraska, USA). The calibration factor (CF) for acetic acid (CH 3 COOH) was estimated from the experimentally determined CF for CH 3 COCH 3 . This is done by considering the calculated collision rate constants of H 3 O + with CH 3 COOH and CH 3 COCH 3 (Su, 1994), the contributions of the protonated molecules to the respective product ion distributions (Schwarz et al., 2009;Inomata and Tanimoto, 2010), 90 and by assuming the same hs-PTR-MS transmission efficiency for ions with a mass difference of 2 u. Similarly, the CF of HCOOH was determined from the measured one of acetaldehyde. The humidity dependence of formic and acetic acid CFs obtained at similar hs-PTR-MS operating conditions has been reported in literature (Baasandorj et al., 2015) and has been taken into account for quantification. By considering the uncertainties on the different parameters involved in the carboxylic acid quantification in the present study, the total uncertainty on their mixing ratio is estimated at 50%. Measurements were 95 averaged over 1 hour to lower the limit of detection (LoD) and the random fluctuations of the measurements. A list of masses, and their associated compound(s), recorded by the hs-PTR-MS together with the LoD, dwell time and whether the compounds are directly calibrated is shown in Table 2.

Ground-based remote sensing
The University of Colorado Multi-AXis Differential Optical Absorption Spectroscopy (CU MAX-DOAS) instrument consists 100 of a scanning (horizon -zenith -horizon) telescope coupled to two ultraviolet-visible grating spectrometers (Coburn et al., 2011). Scattered-light solar spectra are collected along lines of sight at different elevation angles above the horizon (Hönninger et al., 2004), and analyzed using DOAS least-square fitting (Platt and Stutz, 2008) to retrieve trace gas slant column densities (SCD) by the QDOAS software package (Danckaert et al., (accessed June 10, 2019). For this analysis, NO 2 (Vandaele et al., 1998) and O 2 -O 2 (Thalman and Volkamer, 2013) were retrieved in a fitting window from 425 -490 nm, using the further fit 105 settings as described in Kreher et al. (2020). Near-surface volume mixing ratios of NO 2 were retrieved from limb (0 • elevation angle) spectra following Dix et al. (2016). This approach takes advantage of the fact that the limb viewing geometry is highly sensitive to absorbers near instrument altitude. O 2 -O 2 is used to parameterise aerosol extinction near instrument altitude, avoiding the need for complex aerosol profile information (Sinreich et al., 2013;Dix et al., 2016). The NO 2 profile shape was constructed using a typical tropical background with BB enhancements collocated to excess CO from FLEXPART (see 110 section 2.3.2). Variations on the retrieval settings and profile assumptions indicate that ∼10 pptv NO 2 can be quantified with an uncertainty of 5 pptv using this approach. Further tests using NO 2 and O 4 fits at shorter wavelengths (Kreher et al., 2020) determined that the retrieved NO 2 volume mixing ratios generally agree within the reported uncertainty, despite the different spectral ranges average NO 2 over different horizontal spatial scales. This indicates that the NO 2 mixing ratio is representative of the regional lower troposphere predicted by the CAMS model.

Enhancement ratios
The impact of BB events on an atmospheric species X is often quantified by an emission factor (EF X ) or an enhancement ratio relative to a compound Y (EnR X/Y ). The first is defined as the mass of compound X that is released by burning 1 kg of dry fuel, whereas the second is defined as the excess mixing ratio -due to BB -of compound X (∆X), with respect to that of a reference species Y (∆Y). If the EnR is measured close to the source and/or if both X and Y were minimally affected by 120 4 https://doi.org/10.5194/acp-2020-637 Preprint. Discussion started: 10 August 2020 c Author(s) 2020. CC BY 4.0 License. physico-chemical interactions, it is also referred to as the emission ratio of compound X normalised to Y (ER X/Y ). The ER can be computed from the EF by taking the molecular weights (MW) of both species into account: A list of EFs with the associated fuel type has been compiled most recently by Andreae (2019). When comparing the EnR values derived from our observations to ERs from literature, production/loss of plume constituents during transport should 125 be taken into consideration. Enhancement and emissions ratios are often used with CO as the reference species Y. Hereafter, enhancement ratios are always considered with respect to CO unless specifically stated otherwise.
Excess mixing ratios are determined above the background -unaffected by BB -diel profiles which were approximated by the seasonal median diel profiles (appendix A2). During the day, mesoscale transport at La Réunion results in the observatory being located in the planetary boundary layer (PBL). The chemical composition of the PBL is determined by marine, biogenic 130 and anthropogenic sources and sinks interacting in physicochemical atmospheric processes. At night, air masses arriving at RUN originate primarily from the free troposphere (FT). This mesoscale transport results in a natural diel variation of compound mixing ratios which needs to be taken into account when calculating EnR.

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Below we discuss the model simulations used in this study. Each model is used with a specific goal in mind. First, we evaluate the CAMS NRT atmospheric composition service using in situ measurements. It is important that CAMS correctly reproduces CO concentrations at RUN as pyrogenic emissions used in this service will be used to calculate transport of excess CO (∆CO) over the SWIO with the Lagrangian FLEXible PARTicle dispersion model, FLEXPART (Stohl et al., 1998;Stohl and Thomson, 1999;Stohl et al., 2005;Pisso et al., 2019). We use FLEXPART to calculate the mean plume ages during the BB episodes at 140 RUN but also to calculate the impact of pyrogenic emissions on the pristine MBL over the SWIO. Finally FLEXPART-AROME (Verreyken et al., 2019) is used to simulate mesoscale transport in complex terrain towards the observatory. This last simulation is performed in an effort to quantify the PBL-FT mixing during BB intrusions and identify the main transport mode of the plumes.

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We used modelled mass mixing ratios at the location of RUN calculated on different pressure levels (1000, 950, 925, 900, 850, 800, 700 and 600 mbar levels) every three hours (0, 3, 6, 9, 12, 15, 18, 21 UT) from the midnight forecast at 0.5 • × 0.5 • resolution 1 . The CO, O 3 and NO 2 mass mixing ratios are transformed to volume mixing ratios and compared to the in situ measurements. Age classes (AC) are used to estimate the mean plume age (T ) for the different intrusions. The CO plumes are categorised by age with 2 day resolution (T AC = 1 ± 1, 3 ± 1, .., 23 ± 1 days). BB plume excesses are traced for 24 days, after which the plume is assumed to be diluted to negligible background levels. The mean BB plume age is obtained from the FLEXPART output by:

FLEXPART
where ∆CO j is the mean mixing ratio calculated by FLEXPART with AC=j.
To estimate the impact of BB on the MBL for compound X, we use: where ∆CO is calculated by FLEXPART and EnR X is inferred from data. In this approach, the role of an ocean sink is 175 neglected.

FLEXPART-AROME
FLEXPART-AROME 24-hour backtrajectory simulations are used to estimate the respective contribution of the PBL and the free troposphere to the in situ measurements at RUN. Lesouëf et al. (2011) characterised the PBL impact on the Maïdo mountain region by using a passive boundary layer tracer initialised in an approximation of the minimal boundary layer. This PBL proxy is defined as 500 m a.g.l., capped at 1000 m a.s.l. Here, the inverse approach is used by calculating the fraction of time air parcels have spent in the PBL-proxy during the 24-hour backtrajectory simulation. This fraction measures the potential impact of surface emissions on the in situ measurements. We will split this fraction up according to surface type (land/ocean) and call the separate components the mixing fraction (MF). Given the lack of a high-resolution anthropogenic emission inventory over La Réunion, we are not able to use the model to quantify mixing ratios unperturbed by BB plumes and instead use the median 185 diel profile as stated in section 2.2.

Data analysis
Six episodes of enhanced CH 3 CN, which is a typical BB compound, were identified in August 2018 and August 2019 (Fig. 1).
The correlation (r) between the excess mixing ratio of the monitored trace gases and ∆CH 3 CN, during the identified intrusions, 190 is shown in Table 3. As dimethyl sulphide (DMS) is only marginally present in pyrogenic emissions (0.0022 -0.05 g emitted per kg dry matter burned from tropical forest and agricultural residue burning respectively (Andreae, 2019)) and has a short atmospheric lifetime (less than 1 day (Blake et al., 1999)), the correlation between ∆DMS and ∆CH 3 CN is not expected to be directly related to the BB emissions. For this reason, compounds that correlated less well with ∆CH 3 CN than ∆DMS were not considered as plume constituents. Plume constituents in this analysis are thus limited to CH 3 CN, HCOOH, CH 3 COCH 3 ,
Mean background (i.e. outside BB episodes) concentrations of plume constituents in austral winter together with the mean excesses during the different BB intrusions (in %) are shown in Table 4. Correlation with CH 3 CN is especially strong for compounds showing large excesses compared to the diel background pattern (illustrated in appendix A2). We note that trace species such as HCHO, acetaldehyde (CH 3 CHO) and methyl ethyl ketone (MEK) show elevated concentrations during the 200 night in BB episodes, which suggests that they are related to BB. However, as the diel patterns for these compounds are subject to strong variability, excesses are poorly characterised during the day and not analysed further here.
For each of the intrusions, the EnR is computed for CH 3 CN, CH 3 OH, CH 3 COCH 3 , C 6 H 6 , HCOOH, CH 3 COOH and O 3 . Figure 1 shows the scatter plots correlating the excess of the trace species monitored by the hs-PTR-MS instrument and ∆CO.
The calculated EnRs are found in Table 5.

CAMS near-real-time model simulations
The modelled mixing ratios at RUN calculated by the CAMS NRT service are compared to data recorded at the observatory 215 for CO, O 3 and NO 2 (Fig. 3). The model bias for CO, during the BB intrusions, is lowest on the 800 mbar pressure level (bias of 9.7 ppbv), which is closest to the mean pressure measured at the observatory during the same period (792.8 mbar). Note that CAMS reflects well the CO mixing ratios at Maïdo both during and outside (5.1 ppbv bias) BB episodes. As CO is a chemically stable compound in the atmosphere, the agreement between model and measurements indicates that synoptic scale transport and mesoscale mixing with the BB plumes at the location of RUN is sufficiently reproduced by the CAMS NRT model.

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The O 3 model bias is 16 ppbv during the BB episodes with a maximum bias of 39 ppbv (67% above the calculated value). Outside the BB episodes, the CAMS O 3 concentrations show only a small bias (0.8 ppbv), within the uncertainty of measurements.
This good agreement outside of the BB events suggests that mesoscale O 3 sources and sinks either have a limited impact or are correctly calculated by the model at the location of RUN.
The NO 2 bias reaches 60 pptv during BB episodes, while it is only 9 pptv (within 10 pptv DOAS accuracy error) in other 225 periods. Note that the NO 2 measurements are from the ground-based remote sensing CU MAX-DOAS instrument and reflect the NO 2 mixing ratio in the lower free troposphere. The large discrepancy in modelled and measured NO 2 on 3 August 2019 may be due to a weak BB plume passing near RUN (appendix B).

FLEXPART forward simulation
A comparison between ∆CO obtained from measurements and the calculated ∆CO from transport of GFAS v1.2 emission The relative humidity during the BB intrusions was generally low (see Fig. 2). Peak RH values correspond to large impact of the MBL and often lower ∆CH 3 CN concentration (e.g. 7 and 17 August 2019, Fig. 2). From this, we expect the plume to be primarily located in the free troposphere, which is drier than the PBL. This is consistent with results from FLEXPART ( Fig.   4), where ∆CO is especially significant in layers above 1500 m a.g.l. The primary sink in the FT during austral winter (dry season) is due to photochemical interaction. This is also evident from the CAMS NRT model where elevated CO mixing ratios 250 are calculated between the 850 mbar and 700 mbar pressure levels (∼ 1500 -3000 m a.s.l.).

Plume characterisation
The emission ratios are computed based on emission factors from (Andreae, 2019) for CH 3 CN, HCOOH, CH 3 COOH, CH 3 COCH 3 , C 6 H 6 and CH 3 OH are shown in Table 6. Possible fuel types for BB plumes arriving at RUN are: savanna and grassland, tropical forest or agricultural residue. Enhancement ratios are compared to the emission ratios to check for consistency with accepted 255 knowledge regarding sources/sinks during transport.

Acetonitrile, acetone, methanol and benzene
During the synoptic scale transport in the free troposphere, the photochemical sink is expected to be dominant over wet scavenging. As the lifetime with regards to this sink is larger than the maximum plume age (13.7 days) for both CH 3 CN (τ CH3CN = 260 1.4 years (de Gouw et al., 2003)) and CH 3 COCH 3 (τ CH3COCH3 = 36 -39 days (Arnold et al., 2005;Fischer et al., 2012)), the EnRs are expected to correspond well with the ERs from literature. This is the case for CH 3 CN (Table 6). In contrast, the EnR of acetone (∼ 8 pptv ppbv −1 ) is at least a factor of ∼ 2 larger than the ER from the literature (Table 6), a likely indication of secondary CH 3 COCH 3 formation in the BB plume. Acetone production has been recorded in BB plumes over the Eastern Mediterranean (Holzinger et al., 2005) and over Namibia (Jost et al., 2003). In contrast, aged BB plumes over Eastern Canada 265 and Alaska did not show evidence of acetone production (de Gouw et al., 2006). Known pyrogenic CH 3 COCH 3 precursors are propane, i-butane and i-butene (Singh et al., 1994). Using the EFs from Andreae (2019), we find ER propane = 1.2 -3.2 pptv ppbv −1 , ER i−butane = 0.05 -0.1 pptv ppbv −1 and ER i−butene = 0.30 -0.52 pptv ppbv −1 . Taking these known precursors of secondary CH 3 COCH 3 into account, as well as acetone formation yields at high NO x estimated based on the Master Chemical Mechanism MCMv3 (http://mcm.leeds.ac.uk/MCM/) (Saunders et al., 2003), the secondary production of acetone 270 can be estimated. It is found to enhance the acetone EnR by 1.16 -2.80 pptv ppbv −1 , therefore explaining the major part of the discrepancy. This is at odds with results from Jost et al. (2003) where fast CH 3 COCH 3 production is observed and propane could not be considered as a precursor since this conversion is a slow process.
Both methanol and benzene have shorter expected lifetimes compared to the age of the BB plume arriving at RUN (τ CH3OH = at RUN compared to the reported average emission ratios from literature (Table 6).

Carboxylic acids
Due to the relatively short global average atmospheric lifetime of HCOOH (τ HCOOH = 2 -4 days (Stavrakou et al., 2012)) and CH 3 COOH (τ CH3COOH ≈ 2 days (Khan et al., 2018)), EnRs in aged BB plumes should not be compared to emissions ratios 280 from literature (Paulot et al., 2011). However, as wet-and dry deposition are dominant sinks for both CH 3 COOH and HCOOH, their effective lifetime during transport in the FT is expected to be much longer (τ HCOOH ≈ 25 days from photochemical oxidation (Millet et al., 2015)).
The yield of HCOOH from glycolaldehyde oxidation has been measured to be 18% at 296 K and 52% at 233 K (Butkovskaya et al., 2006). This may account for part of the HCOOH production during transport. However, recent studies indicate that this production is effective only in high NO x conditions that are not realistic in a natural environment (Orlando et al., 2012;Orlando and Tyndall, 2020). Production of HCOOH from glycolaldehyde is thus most likely only a minor source. No other 290 known precursors were identified to account for the high HCOOH production during transport to RUN suggesting a missing source in current knowledge.
Secondary production of HCOOH was also found in BB plumes over Canada (Lefer et al., 1994) but was not observed in previous ground-based FTIR studies at La Réunion (Vigouroux et al., 2012). Enhancement ratios of HCOOH calculated from the Tropospheric Emission Spectrometer instrument aboard the NASA's aura spacecraft over Africa ranged from 26 to 28 pptv As these EnRs are inferred from data over biomass burning hotspots in Africa, HCOOH is probably formed primarily close to the source and conserved during synoptic scale transport towards RUN.
For CH 3 COOH the enhancement ratio (EnR CH3COOH ≈14 pptv ppbv −1 ) is of the same order of magnitude as the emission 300 ratios from literature (Table 6). Therefore, in contrast with the case of HCOOH, no significant secondary production of acetic acid in BB plumes is identified.

Ozone and NO 2
It is generally accepted that O 3 is produced in BB plumes during transport (Taupin et al., 2002;Jaffe and Wigder, 2012; Par- Ozone production in BB plumes tends to be NO x -limited (Jaffe and Wigder, 2012). The measured NO 2 mixing ratio during BB episodes is significantly higher than those calculated by CAMS (Fig. 3) contributors to the misrepresentation of O 3 mixing ratios at the location of RUN.

Plume dispersion over the SWIO
Transport of BB plumes recorded by the hs-PTR-MS at RUN takes place primarily in the lower FT. This implies that dispersion of the plume into the MBL is possible through turbulent mixing in shallow cumulus clouds and development of the MBL.
330 Figure 5 shows ∆CO due to pyrogenic emissions from plumes between 4 and 16 days old (corresponding to the extremes of plume ages observed at Maïdo) as calculated with FLEXPART on the model output layer 0 -500 m a.g.l. By using equation 3, estimates of ∆CH 3 CN, ∆CH 3 COCH 3 , ∆CH 3 OH and ∆C 6 H 6 in the pristine marine boundary layer environment were made (Fig. 5) The low variability in EnRs, between different BB intrusions at RUN, for both CH 3 CN and CH 3 COCH 3 allows for characterisation of mixing ratios in the marine boundary layer with small relative uncertainties (8.3% and 13.5% respectively). The 345 local impact of ∆CH 3 CN in the SWIO MBL during the August BB episodes (∼ 50 pptv) constitutes an increase of ∼ 60 -150% over the SWIO as measured during the MANCHOT campaign (zone I: 80±20 pptv, zone III: 20±10 pptv). Acetone excesses are based on the assumption that acetone production in the BB plume is similar in the free troposphere and in the marine boundary layer. The excesses over the SWIO can reach up to 300 pptv, ∼ 30 -75% above the backgrounds recorded during MANCHOT.

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The relatively short lifetimes of CH 3 OH and C 6 H 6 result in a larger variability of the enhancement ratios between different BB intrusions. This is reflected in the larger relative uncertainty in the calculated excesses over the SWIO (21.7% and 32.6% for CH 3 OH and C 6 H 6 respectively). Calculated ∆CH 3 OH over the SWIO are ∼ 0.5 ppbv, corresponding to an increase of 25% (zone I) to at least 100% (zone III) compared to the values recorded during MANCHOT (Colomb et al., 2009). The expected ∆C 6 H 6 over the SWIO is 30 pptv. This is only a minor increase compared to zone I of the MANCHOT campaign (160±40 355 pptv) but constitutes a significant increase (150%) in zone III, further south over the SWIO.
Due to the short lifetime of carboxylic acids in the humid marine boundary layer, the method used above to estimate the BB impact on the SWIO is not valid for HCOOH CH 3 COOH.

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We have shown that BB plumes were recorded with the hs-PTR-MS instrument deployed at the high-altitude Maïdo observatory located in the South-West Indian Ocean. Six different episodes of biomass burning plumes have been identified and studied in August 2018 and August 2019. Enhancement ratios relative to CO have been calculated for CH 3 CN (1.61 -2.06 pptv ppbv −1 ), HCOOH (17.5 -33.8 pptv ppbv −1 ), CH 3 COCH 3 (6.84 -10.0 pptv ppbv −1 ), CH 3 COOH (9.8 -18.0 pptv ppbv −1 ), C 6 H 6 (0.27 -0.83 pptv ppbv −1 ), CH 3 OH (8.7 -18.8 pptv ppbv −1 ) and O 3 (410 -640 pptv ppbv −1 ). Comparison between these EnRs 365 and the ERs calculated from literature showed production of CH 3 COCH 3 and HCOOH. Secondary production of CH 3 COCH 3 was accounted for by pyrogenic emission of precursor species propane and to a lesser extent i-butane and i-butene. Production was especially significant for HCOOH with EnRs about 10 times larger than the ERs. This HCOOH production can not be accounted for by known precursor species.
The CAMS NRT atmospheric composition service was shown to reproduce well the CO concentrations at RUN both during identify the different ageing mechanisms during transport in the MBL compared to transport in the FT. This would be especially valuable for CH 3 COCH 3 and CH 3 OH, for which the role of the ocean on the total atmospheric budget remains uncertain.
Other data is available upon request. Competing interests. The authors declare that they have no real or perceived conflicts of interests.
Acknowledgements. This research has been supported by the "Belgian Research Action through Interdisciplinary Networks" (BRAIN-be)

A1 Seasonal biomass burning profile
Hourly averages of CO and CH 3 CN are shown in Fig. A1. Both CO and CH 3 CN have large peak values from August to November. This corresponds to the biomass burning season as determined from ground-based remote-sensing data studies performed at La Réunion (Duflot et al., 2010;Vigouroux et al., 2012). The analysis presented in this study focuses on the first biomass burning intrusions measured for each season. The motivation for this choice is that the variability in diel profiles 405 between different days is less pronounced during this period and backgrounds do not suffer from accumulated BB tracers for compounds with long atmospheric lifetimes.

A2 Austral winter variation of in situ measurements at RUN
The temporal evolution of biomass burning plume constituents during austral winter 2018 and austral winter 2019 are shown together with the diel distribution of hourly averaged mixing ratio from Fig. A2 to Fig. A10. The median diel profile is used as 410 an estimate of background variation above which the biomass burning excesses are determined. This works especially well for compounds with relatively small variability between different days compared to the excesses due to biomass burning (e.g. CO, CH 3 CN, HCOOH, CH 3 COCH 3 and CH 3 COOH) but may introduce errors for other compounds (e.g. C 6 H 6 , CH 3 OH and O 3 ).
When this difference becomes negligible, the analysis no longer works and these compounds are not considered (e.g. HCHO and CH 3 CHO).

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Appendix B: NO 2 coincidence with FLEXPART simulations NO 2 volume mixing ratios from the CU MAX-DOAS instrument are generally lower than 100 pptv outside of the BB episodes.
A notable exception to this is 3 August 2019 when it reaches ∼ 280 pptv. This coincides with slightly elevated ∆CO signals simulated by FLEXPART at RUN (Fig. A11). At the visible wavelengths, the horizontal spatial scale probed is about 40 km and the overlap with the PBL is only a few km. As a results, measurements from the CU MAX-DOAS instrument are expected 420 to compare well to the FLEXPART and CAMS models which have a low spatial resolution. Remark that when the NO 2 mixing ratio from the CU MAX-DOAS instrument is above 100 pptv, FLEXPART ∆CO is generally enhanced between 1000 -1500 m a.g.l.
As the plume on 3 August is not clearly observed in the in situ measurements we assume that it is not well mixed with boundary layer air at RUN and do not investigate it further here.     25 https://doi.org/10.5194/acp-2020-637 Preprint. Discussion started: 10 August 2020 c Author(s) 2020. CC BY 4.0 License.