1 Introduction
Biomass burning represents a significant source of aerosol particles on the global scale and thus has a substantial impact on the Earth system. At the regional level, where large-scale and seasonal burning practices are conducted annually, significant anthropogenic perturbations may occur. The Brazilian Amazon rainforest and Cerrado are such regions, where an annual burning season typically running from August to October results in the build-up of a large atmospheric aerosol burden that can affect climate
Biomass burning is the largest source of black carbon (BC) particles when considering the global scale . One of the key complicating factors in relation to BC is the co-emission and subsequent mixing with other chemical components
As well as BC, biomass burning produces abundant emissions of organic carbon species in the gas and particle phase
The goal of this paper is to characterise the transformation and ageing of biomass burning aerosol over the Amazon basin, with a focus on the carbonaceous component. The experimental study was conducted during the airborne component of the South American Biomass Burning Analysis (SAMBBA) during September/October 2012. SAMBBA aimed to investigate the impact of biomass burning in the region on the Earth system and on human health. SAMBBA represented the first airborne deployment of an aerosol mass spectrometer and single-particle soot photometer in Brazil, providing previously unobtainable characterisation of non-refractory aerosol species and BC-containing particles and their microphysical properties with high time resolution and sensitivity. Such measurements allow us to investigate the composition of OA and mixing state of BC as a function of atmospheric ageing for a case study analysis of a large fire plume as well as regional-scale measurements across the Amazon basin. The analysis presented here serves as the bridge between near-source fire emissions characterised by and a regional-scale synthesis by . Compared to previous and subsequent biomass burning seasons, 2012 was a relatively normal year when compared to the past decade , which has seen reduced deforestation compared to the historical record, albeit with less significant reductions in fire count
2 Method
2.1 Instrumentation
All measurements presented here were conducted on the UK Facility for Airborne Atmospheric Measurement (FAAM) British Aerospace 146 (BAe-146) atmospheric research aircraft. As a whole, SAMBBA was composed of 18 science flights conducted between 14 September and 3 October 2012. For the purposes of our regional analysis, we investigate nine of these flights, which focussed on boundary layer sampling of the regional biomass burning haze (see , for a broader discussion and context for SAMBBA). The flights and their operating regions are summarised in Table . The primary base of operations was Porto Velho in Rondônia state.
Table 1
Flight summary of the operations included in this study. All flights were conducted during 2012. Local time (LT) is UTC4. Take-off and land times include airport used: PVH – Porto Velho; PMW – Palmas. The phases correspond to the synoptic meteorological conditions during the study, where relatively dry conditions were prevalent in Phase 1 (P1), before the period when the monsoonal transition was being established in Phase 2 (P2).
Flight | Date | Take-off (LT) | Land (LT) | Phase | Operating region |
---|---|---|---|---|---|
B731 | 14 Sep | 10:00 (PVH) | 14:35 (PVH) | P1 | Rondônia |
B734 | 18 Sep | 08:00 (PVH) | 12:15 (PVH) | P1 | Rondônia |
B737 | 20 Sep | 10:45 (PVH) | 14:45 (PVH) | P1 | Rondônia |
B739 | 23 Sep | 08:00 (PVH) | 12:00 (PVH) | P2 | Rondônia |
B740 | 25 Sep | 07:45 (PVH) | 11:00 (PVH) | P2 | Rondônia |
B742 | 27 Sep | 09:00 (PMW) | 12:30 (PMW) | P2 | Tocantins |
B744 | 28 Sep | 09:00 (PVH) | 12:30 (PVH) | P2 | Rondônia |
B745 | 28 Sep | 14:00 (PVH) | 17:30 (PVH) | P2 | Rondônia |
B746 | 29 Sep | 09:00 (PVH) | 13:00 (PVH) | P2 | Rondônia/Mato Grosso |
The aerosol instrumentation used in this study sampled via Rosemount inlets . These inlets have been shown to be satisfactory for sub-micrometre aerosol measurements , which is typical of the SAMBBA dataset as a whole based on size distribution measurements. Nafion driers were used to dry the aerosol sample, which in combination with ram heating as the sampled air enters the aircraft and decelerates, reduced the measured sample relative humidity to a range from 20 % to 60 %. Losses associated with the Nafion driers represent an additional uncertainty in our measurements, which we do not account for. All concentrations are reported at standard temperature and pressure (STP, 273.15 and 1013.25 respectively) and are denoted with an “s” in their unit where appropriate; for example refers to standard metre cubed.
A Droplet Measurement Technologies (DMT, Boulder, CO, USA) single-particle soot photometer
An Aerodyne Research Inc. (ARI, Billerica, MA, USA) compact time-of-flight aerosol mass spectrometer
Additional information regarding quality assurance procedures for the SP2 and AMS during SAMBBA can be found in .
Carbon monoxide mixing ratios were measured using a vacuum ultraviolet (VUV) fast fluorescence CO analyser, with measurement uncertainties of approximately 2 % .
2.2 Background concentration calculationsExcess mixing ratios and concentrations of individual species , denoted as , are necessary in order to investigate chemically driven changes as well as other processes such as dilution and wet removal. For the following regional-scale analysis, we use the fifth percentile for each species during a straight-and-level run (SLR) as the ambient background values of species to determine . For the case study analysis, we identified the smoke plumes manually based on the time series of CO, OM and rBC and then determined the ambient background values while sampling outside the smoke plumes for each cross-plume SLR using the same method as the regional-scale analysis. Tropospheric mixing can lead to changes in the background air composition, which can lead to uncertainties in the determination of ; our sampling and method aims to mitigate for such changes as our SLRs are relatively short (10–30 min) and within the atmospheric boundary layer, typically sampling a fairly homogenous haze burden over a single SLR or flight. This limits large changes in mixing plus we manually inspect our time series and background values to identify clear shifts due to changing air masses, e.g. large-scale spatial gradients (B734) or wet scavenging (B739), and recalculate background values over shorter flight segments if necessary. For the case study analysis, our measurements are very close to source, and we observed constant background concentrations throughout our plume intercepts. As a result, we expect uncertainties in the determination of to be small.
3 Tropical forest fire case study
The following section presents a case study of a tropical forest fire sampled on flight B737 on 20 September 2012 in Rondônia state. Take-off was at 14:45 UTC (10:45 local time), lasting 3 h 45 min. The state is characterised by tropical moist broadleaf forest, as well as extensive deforestation. A large smouldering tropical forest fire was sampled and is shown in Fig. alongside the flight track of the aircraft during the low-level sampling of the fire and smoke plume. reported near-source measurements of the fire, concluding that the fire was likely natural in origin as it was located well away from deforestation areas and was in a national park many kilometres from the nearest road. They reported a modified combustion efficiency
Figure 2
Time series of altitude, carbon monoxide (CO), organic matter (OM), refractory black carbon (rBC) and inorganic aerosol components during the case study analysis for flight B737. Downwind cross-plume intercepts, the along-plume straight-and-level run (SLR), and fire overpass intercepts across the plume are indicated by the dashed boxes. The fire itself was located on a 900 high plateau.
[Figure omitted. See PDF]
We do not have a quantitative estimate of fire size for the B737 case study, although, based on MODIS hotspot data corresponding to our sample location, the maximum fire size is approximately 5 and was likely smaller during our sampling. Furthermore, based on the velocity of the aircraft and the width of cross-plume intercepts, we estimate that the plume was approximately 3–4 wide in the near field before expanding to approximately 21 when 56 downwind of the fire. The atmospheric stability profile tends towards instability in the flight conditions during our case study, with absolutely unstable air below approximately 2 where the lapse rate is 10.9 and conditionally unstable air from 2 to 3 where the lapse rate is 7.44 .
The time series of gas- and particle-phase species shown in Fig. illustrates the significant enhancements in their concentrations during plume intercepts, as well as the gradual increase in their concentrations as the aircraft approached the fire. CO mixing ratios were in excess of 5000 on the approach to the fire, climbing to over 15 000 when directly above it during the overpass intercepts. OM mass concentrations reached almost 800 on the along-plume SLR and over 3500 during the above-fire intercepts.
Measurements from the along-plume SLR are shown in Fig. relative to the distance from the fire, as well as the approximate age of the plume at the point of sampling. The distance from the fire is calculated as the great circle distance of the aircraft from the latitude and longitude of the fire (approximately 11.0 S, 63.6 W). The age of the plume is calculated using the average wind speed, which was . We note there was a small gradient in wind speed along the length of the plume of 0.02 , corresponding to an average increase of 1.2 along the length of the plume. We omit this from our calculations due to the variability in wind speed also observed, while noting that the latter plume ages reported are potentially biased towards higher values. The plume extended approximately 65 downwind based on the concentrations reaching regional background values, which equates to approximately 3 h in terms of plume age.
Figure 3
Various aerosol chemical and physical parameters as a function of plume length and age for the case study analysis from flight B737. Organic matter (OM), nitrate and sulfate are normalised by carbon monoxide (CO) to account for dilution of the smoke plume downwind. Further details on the calculations are provided in Sects. and . Red star markers on the left-hand side of the figure are averaged across the fire overpass intercepts across the plume with the bars denoting the 2 standard deviation range around the mean value (OM, nitrate and sulfate ratios are taken from ). Individual data points are shown as red circles from the along-plume straight-and-level run (SLR), with a linear regression slope included to illustrate any apparent trends. Slopes of the linear regression are given on the right-hand side of the figure along with their 95 % confidence interval. The correlation coefficient, , is also provided.
[Figure omitted. See PDF]
The evolution of the OM : CO ratio along the length of the plume indicates negligible net change in OM mass downwind of the fire, with the ratio exhibiting a small net decline over the course of the measurements and a low correlation coefficient of 0.16. Compared to the near-source measurements directly above the fire, the OM : CO ratio is slightly enhanced in the near field, although the variability in the above-fire ratio is large relative to the difference. Small net enhancements in sulfate and nitrate relative to CO are observed along the length of the plume, with correlation coefficients of 0.36 and 0.48 respectively. In addition, the along-plume measurements are enhanced relative to the above-fire intercepts. The relative intensity of the organic signal at 44 to the total organic mass, which corresponds to the ion and is denoted as , is used as an indicator for the level of oxidation of the organic aerosol. We observed a substantial increase in along the length of the plume from approximately 0.05 to 0.15, with a correlation coefficient of 0.90. This equates to an increase in of approximately 0.29 to 0.73 over the course of the sampling, which is calculated using the equation from . We observe a small reduction in coating thickness of the rBC-containing particles of with a correlation coefficient of 0.28. The coating thickness observed during the along-plume sampling is lower than that from the above-fire intercepts, although the variability is large in the latter. We do not observe any change in the rBC : CO ratio along the length of the plume sampling; based on the cross-plume intercepts, the mean ratio was , which was lower than the above-fire intercept value of reported in . We observe a minor absolute decrease in rBC core diameter along the plume ( ), with a correlation coefficient of 0.16; the geometric mean mass diameter along the plume was , compared to from the above-fire intercepts. The lower values in the plume run compared to the above-fire intercepts for these rBC parameters may point towards a small shift in the fire conditions, although the variability in the plume is large.
Figure 4
Aerosol mass spectrometer organic mass spectra from different segments of the case study analysis from flight B737. The above-fire mass spectrum is from sampling directly above the fire during a cross-plume intercept, with the two downwind mass spectra measured during the along-plume straight-and-level run (SLR), while the background mass spectrum is in the regional aerosol haze away from the main fire plume study region.
[Figure omitted. See PDF]
Figure shows examples of average OM mass spectra at different stages of the plume's evolution, with approximately 1-order-of-magnitude decreases in concentration. Consistent with the evolution above, the organic aerosol becomes increasingly oxidised downwind of the fire and closely resembles the background regional aerosol after approximately 2.5 h of ageing. Above the fire, 43 dominates (7.6 %), corresponding to CH and CHO ions, with further enhancements from other hydrocarbon peaks, especially 29, 41, 55 and 57. 60, which is associated with levoglucosan and other anhydrous sugars, is also elevated (3.9 % of the organic signal); levoglucosan is often reported as a tracer for biomass burning aerosol. To illustrate the evolution of the mass spectra, we calculate the mean absolute difference between the plume spectra and the background as the square root of the sum of the square differences between their organic peak intensities. We also calculate the linear correlation coefficient between them. The mean absolute difference and correlation between the mass spectrum and the background is 0.0023 and 0.66 respectively, illustrating their similarity. Approximately 1 h downwind, a similar pattern is observed but now with increased signal at 44 (6.2 %), while maintaining the signal at 43 (7.5 %) and reduced signal at the hydrocarbon peaks noted above. The contribution of 60 has reduced to 2.7 % at this point. The mean absolute difference and correlation between the mass spectrum and the background is 0.0016 and 0.87 respectively, illustrating their similarity. After 2.5 h, the contribution from the hydrocarbon peaks has reduced substantially and 44 dominates the organic mass spectrum (13.3 %). The contribution of 44 increases further in the background organic aerosol (15.7 %). The mean absolute difference and correlation between the mass spectrum and the background is 0.00064 and 0.99 respectively, illustrating their similarity. The contribution of 60 has diminished further after 2.5 h (1.0 %), while being close to zero in the background (0.4 %).
The evolution in the organic mass spectra is further illustrated in Fig. , where is compared with and for the plume run and regional background aerosol. Relative to the increase in along the plume and its eventually comparable magnitude to the regional background, initially decreases within approximately the first 45 min of the plume's evolution, before a partial increase and stable magnitude up to the 2 h mark. then increases over the rest of the plume run until reaching the regional background value. The points fall within the and “triangle” space reported by prior studies focussed on organic aerosol less influenced by biomass burning . Comparing and illustrates a gradual reduction in as the plume ages and becomes increasingly oxidised downwind, falling within the space reported by and , who reported a similar linear progression.
Figure 5
Comparison of vs. and during the case study analysis for B737, where refers to the fraction of the organic aerosol mass signal at a given mass-to-charge ratio measured by the aerosol mass spectrometer. Also shown is regional haze data during the same flight. Points from the along-plume straight-and-level run (SLR) are coloured according to the approximate plume age. Dashed lines in the vs. show the triangle space reported by prior studies focussed on organic aerosol less influenced by biomass burning . Dashed lines in the vs. are from previous studies on biomass burning organic aerosol ageing, with the upper line from and the lower line from .
[Figure omitted. See PDF]
4 Regional biomass burning haze analysisThe following section examines regional biomass burning flights during SAMBBA to investigate the ageing and evolution of the carbonaceous aerosol on the regional scale. Following the case study in Sect. , we relate the evolution of the regional OM based on changes in as an indicator of the age of the biomass burning smoke sampled. We couple this with the ratio of rBC to CO as an indicator of the air mass history based on the assumption that both are relatively inert tracers that are strongly controlled by the initial conditions at source; the ratio also provides an indication for the influence of precipitation, which would reduce the rBC mass concentration to a larger extent than CO. Including this ratio in our analysis framework provides a means of isolating net changes in OM mass concentration during ageing from changes driven by air mass history.
We focus on boundary layer regional haze, which is determined based on the procedure outlined in , where near-source plumes were identified based on a series of threshold concentrations for multiple pollutants and then flagged separately. This allows us to exclude such plumes from the wider regional haze that we are interested in here.
Figure 7
Sub-micrometre aerosol chemical composition overview for the regional analysis with the data split into individual flight operations in the regional boundary layer aerosol haze. Data are from straight-and-level runs (SLRs) only with the bars denoting mean concentrations and the text above each bar providing the mass fraction as a percentage. B742 took place over Tocantins, while B746 was primarily over Mato Grosso with some measurements over Rondônia. The rest of the flights were conducted over Rondônia.
[Figure omitted. See PDF]
Figure summarises the aerosol chemical composition for each flight using data from SLRs in boundary layer regional haze. Flight B731 in Rondônia state was the most polluted, with total sub-micrometre mass concentrations of 46 . Lower average concentrations are observed across the remainder of the flights, with B734 in Rondônia and B742 in Tocantins being the next greatest in terms of total sub-micrometre mass concentrations of 18 and 17 respectively. OM dominates the sub-micrometre chemical composition, ranging from 75 % of the total on flight B746 to 86 % of the total on flight B739. Sulfate mass fractions ranged from 3.2 % to 9.7 % and are typically larger than nitrate mass fractions, which generally fell between 1.7 % and 3.9 % with flight B740 as an outlier with 7.7 %. Chloride mass fractions were low, ranging from 0.2 % to 0.6 %. Based on ion balance calculations of the inorganic aerosol species, the aerosol was typically neutralised. rBC mass concentrations varied from 2.0 % to 6.1 % on flights within Rondônia state, with the largest concentrations on flights B731 and B734. Note the data coverage for the SP2 was more limited on flight B731 than the other flights. Average rBC mass concentrations (1.5 ) were greatest on flight B742 in Tocantins, contributing 8.7 % of the total sub-micrometre mass concentration. The largest contribution by rBC was 12.4 % on flight B746, which sampled within both western Mato Grosso and Rondônia.
Figure 8
Comparison of organic matter (OM) with carbon monoxide (CO) across individual flights from the regional analysis. Points are coloured according to the ratio of refractory black carbon (rBC) to carbon monoxide (CO) except for B731 where limited rBC data were available. The black dashed line shows the 0.1 as a consistent baseline for context across all flights, with the solid black lines showing the linear regression for either the whole flight or smaller segments where two lines are shown for a single flight. Red text next to the linear regression lines is the slope of the line of best fit in .
[Figure omitted. See PDF]
Figure illustrates the relationship between excess concentrations of OM and CO for each flight. For additional context, the points are coloured by the ratio of rBC to CO. Broadly speaking, there is a strong linear relationship between OM and CO, with correlation coefficients ranging from 0.57 to 0.98. However, the ratio varies both between and within flights. Variability within individual flights, e.g. B734, B737, B739 and B746, is coincident with differences in the ratio of rBC to CO, which likely reflects differences in air mass history across the region(s) sampled on the flight.
Figure 9
Comparison of the ratio organic matter (OM) to carbon monoxide (CO) vs. across individual flights from the regional analysis. refers to the fraction of the organic aerosol mass signal at a mass-to-charge ratio of 44 measured by the aerosol mass spectrometer. Points are coloured according to the ratio of refractory black carbon (rBC) to carbon monoxide (CO) except for B731 where limited rBC data were available. The grey dashed line shows the 0.1 as a consistent baseline for context across all flights.
[Figure omitted. See PDF]
Figure shows the relationship between the ratio of OM and CO compared with to examine whether the ratio changes with variability in OM oxidation and ageing. Within an individual flight, we observe a limited relationship between the ratio and the level of oxidation of the OM, with predominantly low correlation coefficients ranging from 0.09 to 0.09, except for B734 (0.51) and B740 (0.26). On some flights (B731, B734, B745) there are enhancements for greater than approximately 0.16, although in the case of B734 and B745 they appear at least partially related to a change in the ratio of rBC and CO; the limited SP2 data coverage for B731 precludes analysis, although we note that there is also a reduction in the ratio at greater values. In addition, the uncertainty in the ratio of OM to CO will tend to be larger for low concentrations of either or both, leading to more extreme values; this predominantly occurs for the most aged air masses in terms of . Comparing across all flights, changes in the ratio of OM and CO compared to the level of oxidation appear related to changes in the ratio of rBC and CO, which suggests a link with air mass history and any perceived change in net condensation or evaporation of OM.
Figure 10
Comparison of vs. from the regional analysis across individual flights, where refers to the fraction of the organic aerosol mass signal at a given mass-to-charge ratio measured by the aerosol mass spectrometer. Points are coloured according to the ratio of refractory black carbon (rBC) to carbon monoxide (CO) except for B731 where limited rBC data were available. Dashed lines show the triangle space reported by prior studies focussed on organic aerosol less influenced by biomass burning .
[Figure omitted. See PDF]
Figure 11
Comparison of vs. from the regional analysis across individual flights, where refers to the fraction of the organic aerosol mass signal at a given mass-to-charge ratio measured by the aerosol mass spectrometer. Points are coloured according to the ratio of refractory black carbon (rBC) to carbon monoxide (CO) except for B731 where limited rBC data were available. Dashed lines are from previous studies on biomass burning organic aerosol ageing, with the upper line from and the lower line from .
[Figure omitted. See PDF]
Figures and examine compared with and in a similar manner to Fig. in Sect. . The majority of the regional haze data shown in Fig. fall within the triangle space reported by prior studies focussed on OM less influenced by biomass burning . Some flights display a broader range of values suggesting that the flights sampled a more diverse range of air masses in terms of their chemistry and ageing. The behaviour described in Sect. in relation to the evolution during the early stages of the plume's age is present in flights B731, B742 and B745, which suggests sampling of fresher biomass burning smoke on those flights; on flights B742 and B745, such features are distinct in terms of the ratio of rBC and CO as well. In terms of the and space shown in Fig. , the regional sampling is predominantly confined to lower values, as well as displaying the linear tendency noted for the case study in Sect. and previous work
Figure 12
Histograms of refractory black carbon coating thickness from the regional analysis across individual flights.
[Figure omitted. See PDF]
Figure presents histograms of the median rBC coating thickness across the individual flights, which appears to vary appreciably from flight to flight, as well as within some individual flights. The lowest coating thicknesses we observe are in the range from 10 to 20 nm on our case study flight, with regional measurements typically ranging from 40 to 120 nm; such observations indicate that the vast majority of rBC-containing particles within the boundary layer are at least partially coated. We found no clear and consistent relationship between coating thickness and across the dataset. The broad bimodal-like structure in coating thickness in flight B737 could be linked with differences in the ratio of rBC and CO, with the thicker coatings of 80–100 associated with a larger ratio; conversely, the thinner coatings of less than 60 are coincident with the smaller ratios observed. However, there was no clear pattern in this linkage in flights B740 and B744, which also had a bimodal-like structure in coating thickness. Regional-scale variability in rBC coating thickness appears to be predominantly driven by fire-source and/or air mass differences rather than ageing of the aerosol population after emission. We also observed no clear link between the physical size of the rBC core and , with geometric mean mass diameters typically between 250 and 290 .
5 DiscussionWhether considering the case study analysis in Sect. or regional analysis in Sect. , we observe either limited or no net enhancement in the ratio of OM to CO. However, we do observe substantial increases in , which is interpreted as an indicator for the content of the OM. Such a trend with atmospheric ageing is consistent with SOA being produced downwind of source following dilution but that this is approximately balanced by the loss of POA emitted at source. A number of studies have observed such features in other biomass burning environments and hypothesised such a process
examined the role of a number of factors that could control SOA production in ambient plumes, including fire area as a driver of dilution rate, mass emission flux and atmospheric stability. Based on , our estimated initial fire size and atmospheric stability conditions would lead to some evaporation of OM in the near field but with significant SOA production downwind that could balance the initial loss of particulate matter, which would be consistent with our observations of limited net enhancement in OM. Based on thermodynamic analysis of the SAMBBA experiment by , our regional sampling was typically conducted in unstable air, which is consistent with our observed limited net enhancement in OM.
Aqueous processing of biomass burning emissions has been identified as a potential source of SOA
Our regional analysis illustrates the importance of evaluating changes in the ageing of regional OM within a framework that also accounts for differences in air mass history. Differences in vegetation, fire dynamics and environmental conditions can result in significant diversity in the absolute and relative emissions of different pollutants from biomass burning that will manifest in the regional aerosol burden. We also observe significant variability from flight to flight, even within the same region, that is likely a consequence of differing meteorological conditions e.g. the influence of precipitation, as well as changes in fire dynamics. Were we to interpret our observed changes in the ratio of OM to CO as a function of , we would see enhancements of 2–3 in some instances that are most likely driven by differences in air mass history and fire dynamics rather than chemical processing – rBC : CO was key in illustrating such differences where enhancements in OM to CO were often easily distinguished by large changes in rBC to CO.
Our results indicate that uncertainties in the magnitude of the aerosol burden most likely lie in quantifying emission sources, alongside atmospheric dispersion, transport and removal rather than chemical enhancements in mass. Across our study, OM : CO ratios range from 0.029 to 0.13 in the west of the Amazon basin, with a value of 0.095 in the Cerrado environment sampled on flight B742. Numerical models that attempt to represent the magnitude of the atmospheric aerosol burden typically use fixed emission factors for distinct ecosystems; for example those used in the fourth version of the Global Fire Emissions Database
In terms of inorganic species, we observe small net enhancements in sulfate and nitrate relative to CO in the case study analysis. We do not observe clear enhancements in nitrate at the regional scale, while we do observe minor absolute increases in sulfate on some flights.
Aside from the comparison between the above-fire intercepts and the along-plume sampling in the case study, we do not observe clear changes in rBC coating thickness with plume age. Our observations indicate that rBC is rapidly coated in the near field based on our case study, as well as other near-field sampling during SAMBBA, in contrast to many urban sources and environments
6 Conclusions
We observe limited to no enhancement in OM mass production during atmospheric ageing of biomass burning over Brazil for both a case study of a likely natural tropical forest fire and regional sampling over the Amazon and Cerrado. Variability in the ratio of OM to CO is predominantly driven by regional differences likely related to changes at the initial fire source, as well as air mass differences likely as a consequence of wet scavenging of the aerosol. What enhancements we do observe are small in absolute terms compared to regional-scale variability across our study. Such variability at the regional scale can be significant, with flight-averaged OM : CO ratios ranging from 0.075 to 0.13 across our study region in cases where we suspect the influence of precipitation to be minor. We did not observe a systematic difference between the west of our study region and the Cerrado in terms of OM : CO, although we only have one flight in the latter region. While significant, we note that the scale of the variability is much smaller than typical factors required to match satellite and ground-based observations of aerosol optical depth to numerical model estimates of the aerosol burden. We do observe substantial changes in the chemical composition of OM, with significantly increased oxidation downwind, implying SOA formation that is being balanced by evaporation of OM. During our case study, we observed an increase in of approximately , reaching a plateau after approximately 2.5–3.0 h of atmospheric ageing and a comparable magnitude to the background regional aerosol. Such changes may enhance the hygroscopicity of the OA, and given its dominance of the aerosol burden (75 %–86 % of the sub-micrometre mass in our study), this will have implications for the life cycle and radiative impact of biomass burning aerosol in the region.
We observe limited changes in the microphysical properties of rBC subsequent to emission, with neither significant changes in particle core size nor significant changes in coating thickness. We observe substantial coatings on rBC-containing particles at source. Given the limited changes with ageing, our results suggest that any absorption enhancements will be dictated by the initial conditions in the near field and precipitation influences, rather than ageing, although we have not investigated particle morphology changes that may occur. Such coatings likely reduce the lifetime of rBC as they are likely to be at least mildly hygroscopic, especially compared to uncoated hydrophobic rBC particles.
The complex nature of the regional aerosol and its drivers implies that aggregating our observations from the entire study as a function of atmospheric ageing is unwise due to the many conflating and competing factors present. The continuing puzzle over the contrasting observations of the evolution of OM:OC ratios with atmospheric ageing remains, although our results appear consistent with the framework presented by . Further detailed quantification of the processes driving these should be further explored in the literature, as well as chamber and ambient studies specifically designed to probe such processes.
Overall, our results suggest that the initial conditions are the biggest driver of carbonaceous aerosol composition and physical properties in the region, aside from significant oxidation of OA during atmospheric ageing. Uncertainties in the magnitude of the aerosol burden and its impact most likely lie in quantifying emission sources, alongside atmospheric dispersion, transport and removal rather than chemical enhancements in mass.
Data availability
All raw time series data from the FAAM research aircraft are publicly available from the Centre for Environmental Data Analysis (
Author contributions
WTM analysed the data and wrote the paper. JDA, ED, JL and DL provided additional data analysis support, including data processing and quality assurance. SB and JL operated the gas-phase instruments, while JDA and MJF operated the aerosol instruments during the field campaign. BJ, JH, KML, PEA and HC led the planning of the field campaign and were co-principal investigators on the SAMBBA project.
Competing interests
The authors declare that they have no conflict of interest.
Acknowledgements
We would like to acknowledge the substantial efforts of the whole SAMBBA team before, during and after the project. Active fire data were produced by the University of Maryland and acquired from the online Fire Information for Resource Management System (FIRMS;
Financial support
Eoghan Darbyshire was supported by a NERC studentship (grant nos. NE/J500057/1 and NE/K500859/1). This work was supported by the NERC SAMBBA project (grant no. NE/J010073/1). Paulo E. Artaxo was supported by FAPESP (Fundação de Amparo à Pesquisa do Estado de São Paulo; grant nos. 2017-17047-0 and INCT 2014/50848-9). This research was also supported by the LBA (the Large Scale Biosphere-Atmosphere Experiment in Amazonia) central office, operated by INPA (Instituto Nacional de Pesquisas Espaciais).
Review statement
This paper was edited by Sergey A. Nizkorodov and reviewed by three anonymous referees.
You have requested "on-the-fly" machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Show full disclaimer
Neither ProQuest nor its licensors make any representations or warranties with respect to the translations. The translations are automatically generated "AS IS" and "AS AVAILABLE" and are not retained in our systems. PROQUEST AND ITS LICENSORS SPECIFICALLY DISCLAIM ANY AND ALL EXPRESS OR IMPLIED WARRANTIES, INCLUDING WITHOUT LIMITATION, ANY WARRANTIES FOR AVAILABILITY, ACCURACY, TIMELINESS, COMPLETENESS, NON-INFRINGMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Your use of the translations is subject to all use restrictions contained in your Electronic Products License Agreement and by using the translation functionality you agree to forgo any and all claims against ProQuest or its licensors for your use of the translation functionality and any output derived there from. Hide full disclaimer
© 2020. This work is published under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Abstract
We present a range of airborne in situ observations of biomass burning carbonaceous aerosol over tropical South America, including a case study of a large tropical forest wildfire and a series of regional survey flights across the Brazilian Amazon and Cerrado. The study forms part of the South American Biomass Burning Analysis (SAMBBA) project, which was conducted during September and October 2012. We find limited evidence for net increases in aerosol mass through atmospheric ageing combined with substantial changes in the chemical properties of organic aerosol (OA). Oxidation of the OA increases significantly and rapidly on the scale of 2.5–3 h based on our case study analysis and is consistent with secondary organic aerosol production. The observations of limited net enhancement in OA coupled with such changes in chemical composition imply that evaporation of OA is also occurring to balance these changes. We observe significant coatings on black carbon particles at source, but with limited changes with ageing in both particle core size and coating thickness.
We quantify variability in the ratio of OA to carbon monoxide across our study as a key parameter representing both initial fire conditions and an indicator of net aerosol production with atmospheric ageing. We observe ratios of 0.075–0.13
Our study explores and quantifies key uncertainties in the evolution of biomass burning aerosol at both near-field and regional scales. Our results suggest that the initial conditions of the fire are the primary driver of carbonaceous aerosol physical and chemical properties over tropical South America, aside from significant oxidation of OA during atmospheric ageing. Such findings imply that uncertainties in the magnitude of the aerosol burden and its impact on weather, climate, health and natural ecosystems most likely lie in quantifying emission sources, alongside atmospheric dispersion, transport and removal rather than chemical enhancements in mass.
You have requested "on-the-fly" machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Show full disclaimer
Neither ProQuest nor its licensors make any representations or warranties with respect to the translations. The translations are automatically generated "AS IS" and "AS AVAILABLE" and are not retained in our systems. PROQUEST AND ITS LICENSORS SPECIFICALLY DISCLAIM ANY AND ALL EXPRESS OR IMPLIED WARRANTIES, INCLUDING WITHOUT LIMITATION, ANY WARRANTIES FOR AVAILABILITY, ACCURACY, TIMELINESS, COMPLETENESS, NON-INFRINGMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Your use of the translations is subject to all use restrictions contained in your Electronic Products License Agreement and by using the translation functionality you agree to forgo any and all claims against ProQuest or its licensors for your use of the translation functionality and any output derived there from. Hide full disclaimer
Details






1 Department of Earth & Environmental Sciences, University of Manchester, Manchester, UK
2 Department of Earth & Environmental Sciences, University of Manchester, Manchester, UK; National Centre for Atmospheric Science, University of Manchester, Manchester, UK
3 Facility for Airborne Atmospheric Measurements, Cranfield University, Cranfield, UK
4 Department of Chemistry, University of York, York, UK
5 Met Office, Exeter, UK
6 Met Office, Exeter, UK; College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK
7 National Institute for Space Research (INPE), São José dos Campos, Brazil; now at: NASA Goddard Space Flight Center and USRA/GESTAR, Greenbelt, MD, USA
8 Physics Institute, University of São Paulo, São Paulo, Brazil