Wildfire smoke significantly affects atmospheric composition, chemistry, human health, and radiative balance (Andreae and Merlet, 2001; Yokelson et al., 2008; Akagi et al., 2011; Ford et al., 2018; Gregory et al., 2018; Sokolik et al., 2019; Macsween et al., 2020). Wildfire season duration and intensity are predicted to increase in the future, suggesting a growing influence of biomass burning in coming decades (Fairman et al., 2015; Donovan et al., 2017; Abatzoglou et al., 2019). Volatile organic compounds (VOCs) emitted from biomass burning (BBVOCs) are directly harmful to human health and can contribute to the formation of ozone and secondary organic aerosol (SOA) (Akagi et al., 2012; Keywood et al., 2013; Lawson et al., 2015; Sekimoto et al., 2017). Predictions of BBVOC emissions are complicated by the complexity of combustion and fuel characteristics, and model parametrizations are based on a limited number of field observations (Hatch et al., 2015; Sekimoto et al., 2018).

Australia wildfires emit 7 %–8 % of global biomass burning emissions, producing more volatilized carbon than the United States and Europe, with smoke plumes significantly influencing local and even global air quality (Ito and Penner, 2004; Van Der Werf et al., 2010; Keywood et al., 2013; Lawson et al., 2015). In 2019–2020, Australia experienced its worst wildfire season on record with an estimated 19 million hectares of land destroyed (Filkov et al., 2020). This particular season is now colloquially known as the Black Summer, due to its prolonged intensity and length (October 2019–February 2020). Many of Australia's major cities were blanketed in smoke for weeks at a time, leading to long-term exposure to excessive concentrations of harmful atmospheric compounds (Borchers Arriagada et al., 2020). These fires predominantly affected the temperate forests of the state of New South Wales (NSW), burning the largest land area of anywhere in the country (Davey and Sarre, 2020). Despite the impact on atmospheric composition from Australian fires, its biomes remain understudied, particularly these same NSW forests (Lawson et al., 2015). Given the complexity and variability in biomass burning scenarios and the use of emission factors (EFs, in units of kilograms of VOC emitted per kilogram fuel burnt) to inform air quality models, this can lead to issues in effectively constraining emissions. For example, Lawson et al. (2017) reported a strongly non-linear response in simulated ozone (O3) when varying biomass burning (BB) EFs, showing the resulting sensitivity from chemical transport models (CTMs). This sparseness of measurements leads to the use of North American EFs (such as those from Burling et al., 2011, or Akagi et al., 2011) to inform CTMs, simulating emissions of geographically separate biomes. Even among similar biomes (for instance, the temperate forests of the US), fuel types differ and thus can influence the speciation of VOCs emitted (Coggon et al., 2016; Hatch et al., 2017; Guérette et al., 2018). Further evidence of this is found in a study by Guérette et al. (2018) showing that EFs of some VOCs (e.g., formic acid, ethane, monoterpenes, acetonitrile) can be 3–5 times higher than those measured in the US, and attributing this to fuel type.

A complicating factor in deriving EFs from field observations is accounting for the influence of chemical processing. EFs are ideally based on observations close to the fire. When this is not possible, indicators of plume chemical age, such as oxidized VOC (OVOC) to VOC ratios, can be used to diagnose the relative age of a plume. During the day, downwind VOC concentrations are primarily influenced by OH-initiated oxidation. At night, NO3-initiated oxidation can significantly influence observed VOC concentrations (Decker et al., 2019; Kodros et al., 2020). There are several methods in existence for assessing daytime oxidation, but fewer are known for the night (De Gouw et al., 2006; Liu et al., 2016; Gregory et al., 2018; Decker et al., 2019). In this work, we use the maleic anhydride-to-furan ratio introduced in Gkatzelis et al. (2020) to assess OH oxidation. We examine the use of a new OVOC/VOC ratio, cis-2-butenediol + furanone-to-furan, as an indicator of nighttime oxidation.

To further assess the effects of nighttime transport on biomass burning emissions, we look at the magnitude of OH reactivity measured that results from the compounds which most substantially contribute to it and determine the relative contributions of the resulting chemical groups. Certain categories of BBVOCs like furans or phenols, which are emitted in the combustion process, are important as they enhance OH reactivity and resultingly have high O3 and SOA forming potential, and are considered to be understudied (Gilman et al., 2015; Hatch et al., 2017). Most wildfire studies are conducted during the daytime, with plume oxidation focused on interactions with the OH radical and O3 (Liu et al., 2016; Coggon et al., 2019; Palm et al., 2020; Decker et al., 2021; Permar et al., 2021). However, the plume studied here spent a significant amount of time transported under nighttime conditions.

Additionally, we use time series to observe chemical trends in ozone (O3) and nitrogen dioxide (NO2) as their emissions and chemical behavior are intimately linked with biomass burning chemistry. O3 production in wildfire plumes is contingent on initial emissions, local environment, and atmospheric processing during transportation. Wildfire plumes emit significant precursors of O3, but there is not a general consensus towards generation or depletion, with various campaigns reporting measurements in either case, especially in the instance of processed, downwind plumes (Verma et al., 2009; Alvarado et al., 2010; Jaffe and Wigder, 2012; Lawson et al., 2015; Brey and Fischer, 2016; Müller et al., 2016). NO2 is emitted during the combustion process and has a non-linear relationship to O3 production via reactions with these VOC precursors. However, the NO2 radical has additional chemical pathways with OH, NO3, and phenolic compounds leading to a general NOx-limited regime (Jaffe and Wigder, 2012; Liang et al., 2022; Robinson et al., 2021). Furthermore, there are again fewer observations for the effect of nighttime oxidation processes on O3 production with a recent modeling study conducted by Decker et al. (2019). O3 production in wildfire smoke remains a significant source of uncertainty in its contribution to the tropospheric O3 budget (Jaffe and Wigder, 2012; Young et al., 2018; Xu et al., 2021).

Here, we use observations from a proton-transfer-reaction time-of-flight mass spectrometer (PTR-ToF-MS) during the 2019–2020 Australian wildfire season to derive EFs of 15 compounds, including 6 compounds for which there are no previous observations. We examine a subset of smoke-influenced nighttime observations made by a PTR-ToF-MS during the COALA-2020 field campaign. NO3-initiated oxidation dominated the chemical processing late in the night, as the plume traveled ∼ 8 h to the field site from large, highly active fires to the south. We also use co-located Fourier transform infrared (FTIR) measurements of CO2, CO and CH4 to derive these EFs for nighttime longer-lived VOCs (τBBVOC+NO3 ≥ average transport time). We compare these results with five related studies, two focused on Australian temperate forests, two focused on US temperature forests, and one reporting EFs used to represent temperate biomes across the globe. We find generally good agreement across several of these studies and discuss potential reasons for discrepancies seen in EFs for selected compounds.

Figure 2 shows the observations of CO and VOCs during a smoky period on 3–4 February 2020. CO and acetonitrile – long-lived tracers associated with wildfires (Coggon et al., 2016) – are used to identify the total period of time during which observations were impacted by smoke. Enhancements in both species started at 17:30 LT on 3 February and lasted until 19:00 LT on 4 February, when wind direction shifted.

We use furan, a short-lived smoke tracer, and its oxidation products to determine which periods of the smoke event represent the least oxidized plume. Furan is highly reactive with OH (kOH+furan = 4.04×10-11 cm3 molec.-1 s-1 at 298 K and 1 atm) and NO3 (kNO3+furan = 1.36×10-12 cm3 molec.-1 s-1 at 298 K and 1 atm). OH-initiated oxidation produces maleic anhydride, which has low reactivity with both OH and NO3 (τOH=3.99 d, τNO3=1.42 d with [OH]Avg = 2×106 molec. cm-3 and [NO3]Avg = 8×107 molec. cm-3, with reaction rate constants from Grosjean and Williams (1992) and Bierbach et al. (1994) and no reported direct emissions). The ratio of maleic anhydride-to-furan therefore provides a relative measure of the plume photochemical age. Using aircraft-based observations of wildfire plumes in the western US, Gkatzelis et al. (2020) found that maleic anhydride-to-furan ratios below 0.10 indicate the plume has undergone little OH processing.

Nighttime in-plume furan oxidation is dominated by NO3, with contributions from O3 (Decker et al., 2019). While many BBVOCs are highly reactive with NO3, there is substantially less research on indicators of NO3 oxidation. Decker et al. (2019) track NO3 chemistry using the ratio of total reactive nitrogen (NOy) to NOx, and Kodros et al. (2020) examine NO3-reacted products such as nitrocatechol and nitrophenol of phenolic compounds (e.g., phenol, catechol, cresol). Measurements of NOy were not made during this field campaign, and NO3 products of phenols were subject to high uncertainty due to fragmentation in our PTR-ToF-MS measurement. We therefore examine a new indicator of NO3 processing using furan's dominant NO3 products – cis-2-butenediol and furanone (Berndt et al., 1997). Both products are relatively long lived, with lifetimes estimated at τcis-2-butenediol=9 d and τfuranone=8 h assuming an average concentration of [NO3] = 8×107 molec. cm-3 (O'Dell et al., 2020). Lab-based studies and field campaigns conducted in the US and Australia suggest that furan and furanone EFs are comparable, with study-averaged values for furan ranging from 0.132–0.51 g kg-1 and 0.27–0.57 for furanone (Andreae and Merlet, 2001; Akagi et al., 2011; Hatch et al., 2015; Stockwell et al., 2015; Liu et al., 2017; Koss et al., 2018; Selimovic et al., 2018). No furan EFs have been reported for Australian temperate forests and only one furanone EF is reported from Lawson et al. (2015) at a comparable value at 0.57 g kg-1. Additionally, emissions modeled in Decker et al. (2019) from wildfires suggest that furan and furanone are emitted in roughly equal proportions. As such, we operate not on the assumption of negligible OVOC emissions, but that variability in OVOC/VOC ratios are driven by chemical aging. Cis-2-butenediol and furanone are both measured at m/z 85, and from here onwards will be denoted as such.

Figure 2 shows furan enhancements, which begin later on 3 February than acetonitrile, maleic anhydride, and m/z 85 enhancements, indicating a less oxidized plume was being sampled. Maleic anhydride concentrations are high during the initial period of the smoke event, suggesting significant OH-initiated processing throughout the day before the plume reached the site. After sunrise, furan decays faster than CO, and maleic anhydride concentrations begin to rise, again showing the impact of OH-initiated oxidation. Enhancements in m/z 85 are seen when the smoke arrives and vary throughout the night. Just prior to sunrise (04:00–06:15 LT), both OVOC/VOC ratios rapidly decrease (Fig. 3), corresponding with a rise in furan, CO, and acetonitrile. Maleic anhydride/furan drops to 0.05, which is within the lower range of the chemically younger plumes reported by Gkatzelis et al. (2020). The ratio of m/z 85 to furan is around 2.5. While we cannot use this to quantify plume age since the two products are measured as a sum, we note that this period constitutes the lowest ratio throughout the event, with surrounding periods having ratios 1.6–2.8 times greater. We note that at a value of 2.5, this plume has likely undergone significant aging, despite this being the freshest smoke detected during the campaign. Further corroboration of these results, determined via particulate matter (PM) composition, can be found in Simmons et al. (2022). In their study, a ToF-ACSM was employed and observed the ratio of PM1 mass fraction at mass-to-charge ratio 44 (f44), where a lower mass fraction indicates a less oxidized plume. A similar decrease at f44 in the same timeframe as the m/z 85 and maleic anhydride tracers is noted.

The rapid decreases in OVOC/VOC ratios are unlikely to result from shifts in chemistry alone. Instead, this suggests a shift in meteorological conditions which brings in smoke from a closer source, in agreement with measured wind direction, which shifted from flowing northeast to north at this time. We further investigate plume transport using a back-trajectory model.

We use a HYSPLIT back-trajectory model (Stein et al., 2015) to determine the origin and transport time of the smoke arriving at the site throughout the smoke event. The meteorological input used is the Global Data Assimilation (GDAS) dataset. The model was set to assess trajectories at three different altitudes at 10, 500, and 1500 m above ground level (a.g.l.) to capture plume height. Our period of interest spans from 17:00 LT on 3 February, just before CO enhancements are seen at the site, to 06:00 LT on 4 February when furan concentrations rapidly decrease. The model was set to calculate a new 12 h trajectory every hour during this time. Back trajectories are shown in Fig. 1. For every hour in the event (each represented by a color), one can track the origin of the sampled air mass 12 h in advance of its arrival.

A shift in trajectories occurred between 17:00 and 18:00 LT on 3 February, corresponding with the arrival of the smoke plume as indicated by observed CO enhancements. Subsequent trajectories originate near the fires located ∼ 230–375 km from the field site on the southeast coast. The model shows that air masses initially stayed at low altitude and were lofted to ∼ 560 m a.g.l. when passing over the active fires ∼ 25 km to the south, near Canberra (Fig. S1 in the Supplement). The plume descended to 10 m a.g.l. as it reached the coast. The model suggests smoke sampled later in the evening (between 04:00–06:00 LT on 4 February) spent more time over land compared to previous points in the event. This shift in trajectories and the increasing intensity of fires near Canberra during this time signify possible contributions to the decrease in OVOC to VOC age marker ratios. Further investigation is conducted via HYSPLIT forward trajectories in the supplement (Figs. S2 and S3). In short, during this period, plumes from the Canberra fires were lofted to 2000 m a.g.l. well before crossing with the SE fire plume, which attained a maximum altitude up to 560 m a.g.l. This indicates little influence from the Canberra fires on our measurements. Given that there are two major clusters approximately 70 km apart in the SE, the influence of precipitation and wind speed (Figs. S4–S6) is considered to determine whether combustion conditions were comparable. Both fires experienced similar total precipitation in the month prior and experienced similar wind speeds during this smoke plume event. As a result, we conclude that combustion conditions are similar and that EFs derived from this plume would be representative of a biome average. Over the entire course of the event, HYSPLIT analysis suggests transport time from the fires to the field site is around 8 h (>200 km), but potentially shorter for the time frame immediately prior to sunrise.

Detailed time series of O3 and NO2 are presented in this section in Fig. 4. Information regarding instrumentation and corresponding setups can be found in Sect. 2.1 of Simmons et al. (2022). Like Fig. 2, a CO time series is provided to outline the general trend of smoke during the event.

A non-smoke-influenced daytime and nighttime average (composed of 8 h averages) was calculated for O3 and NO2 concentrations using data from the month of March. Smoke around the continent had been either transported or removed by rain by this time. O3 was calculated to have a daytime concentration of 24.6 ppb and a nighttime concentration of 19.5 ppb. Respective concentrations were calculated for NO2 at 2.2 ppb in the day and 3.3 ppb in the evening. Additionally, averages for a larger suite of gas and aerosol phase variables over all smoke events sampled during the COALA-2020 campaign can be found in Simmons et al. (2022).

As stated before, smoke-related enhancements are visible around 17:30 LT in Fig. 4d, with the hours prior being virtually devoid of tracers. Enhancements pick up without a shift in wind direction, with winds at this time traveling to the northwest, consistent with the HYSPLIT trajectories presented in Fig. 2. As the wind approaches a more easterly direction, enhancements in CO are maintained, and concentrations of more reactive BBVOCs begin to increase. O3 concentration on 3 February reaches a maximum of approximately 25 ppb around 14:00 LT and maintains this level until sunset, when it decreases as biogenic sources are no longer emitting and photolysis is halted. O3 concentration decreases to a minimum 15.6 ppb and NO2 decreases down to 0.8 ppb, both around midnight and both below the nighttime monthly average despite enhancements in CO. O3 has a R2=0.48 with CO and, when considering the known transport time of this smoke, indicates transportation rather than local production. Given the comparatively low concentrations of both compounds at this time, it is likely that this plume is depleting these species. This is compounded with the low concentrations of NO2 in this temperate forest setting and, despite emitting NOx, wildfire plumes being generally NOx-limited (Jaffe and Wigder, 2012; Robinson et al., 2021).

Around 03:30, the wind shifts from traveling northwest to west, significantly enhancing O3, NO2, CO, and total VOC concentrations, corresponding to the least aged portion discussed in Sect. 3. Sunrise occurs around 06:30 LT coinciding with a steady decline in highly reactive VOC enhancements (Fig. 2) and NO2 (Fig. 4c). Liang et al. (2022) found a significant correlation of R2=0.86 between NO2 and maleic anhydride for a transported plume of similar age oxidized in the daytime. The opposite trend is observed in our scenario despite our measurements exhibiting comparable trends from maleic anhydride. The NOx-limited environment and differences in biogenic VOC (BVOC) quantities arising from the forest setting in this study and the urban setting in theirs are likely responsible for the opposing trends in the NO2 time series. Maleic anhydride similarly peaks around noon on 4 February, and both its production and the fast depletion of furan indicate that OH chemical pathways generally oxidize this plume faster than NO3 reaction pathways. While O3 concentration continues to increase after sunrise, it cannot be stated that this is dominantly due to BBVOC oxidation given the strong source of BVOC emissions from the surrounding forest. Isoprene nitrates sequester NO2, ultimately leading to O3 production. The diel cycle of O3 and isoprene on a non-smoke-affected day strongly correlate to temperature and photoactive radiation. O3 does achieve a max concentration of 30 ppb at 12:00 LT on 4 February, which is approximately 5.5 ppb above the daytime average and higher than the prior day despite similar temperatures (23.6 ∘C on 3 February, and 24.5 ∘C on 4 February). This most likely results from the combination of transported O3 compounded with enhanced reactivity from the plume plus local, biogenic-related production. The plume is diluted at a consistent rate until 18:00 LT on 4 February when a shift in wind direction significantly reduces CO enhancements and concludes the smoke event.

As this plume has been shown to oxidize faster when exposed to the OH radical as opposed to the NO3 radical, this indicates that the nighttime transport of this plume would be able to comparably preserve OH reactivity. We investigate this by first determining which compounds were most significant in their enhancements and then determining their corresponding OH reactivity.

First, a subset of the PTR-ToF-MS data was created by calculating ERs using the methodology described in Sect. 6.2 over the same nighttime period. However, we did not filter out compounds by their atmospheric lifetime, and any unidentified species were not considered regardless of correlation strength. This means the resulting OH reactivity is likely to be slightly low, but this method ensures reactivity solely from compounds attributable to BB emissions is being gauged. Then, an average for each compound was calculated using the same period for ERs. These nighttime averages were then compared with their diurnal cycles calculated using data from 1–19 March 2020 (ending date of PTR-ToF-MS sampling ambient air). If a compound's mean over the smokey period is greater than the mean of its diel cycle plus 1σ over the same timeframe, this compound is considered in the transported OH reactivity. Finally, we background correct the nighttime concentrations using the March diurnal cycles and convert to reactivity using Eq. (3): 3ROH=∑[VOCi]⋅A⋅kVOCi+OH, where [VOCi] is the concentration of the ith VOC in units of parts per billion, A is the conversion factor to molec.i cm-3 (A=2.46×1010 in units of molec.air cm-3 ppb-1 at 1 atm and 25 ∘C), and kVOCi+OH is the OH rate constant for the corresponding VOCi. Rate constants were again sourced from the same databases as the NO3 rate constants. The rate constant used for m/z 85 was determined as an average of the constant provided in Koss et al. (2018) (kOH=44.2×10-12 cm3 molec.-1 s-1) and Bierbach et al. (1994) (kOH=52.1×10-12 cm3 molec.-1 s-1) assuming both compounds contributed equally to signal at this mass peak.

Ultimately, 26 compounds were determined to have the most significant contributions, transporting an average OH reactivity of 5.25 s-1, with a minimum of 3.15 s-1 occurring around 03:00 LT on 4 February and a maximum of 9.83 s-1 around 20:00 LT on 3 February, shown in Fig. 6. These values are well within range of those seen in nighttime and aged daytime transported plumes by Liang et al. (2022), who measured a total OH reactivity range from approximately 4–26 s-1. We calculate an OH reactivity from the primary biogenic VOCs (isoprene plus monoterpenes) for further comparison. The maximum biogenic value, achieved around 12:00 LT on 4 February, is 6.35 s-1, and the average biogenic reactivity over the course of the campaign is 5.90 s-1, indicating that the nighttime conditions allowed for the transport of a reactivity quantity that approximately doubled OH reactivity at the COALA-2020 field site. Additionally, there is little variability in the relative contributions to reactivity across these different groups over the course of the smoke event, indicating the plume experienced a consistent oxidation over the course of its travel.

Compounds from the plume have been grouped into four categories to capture their diversity. Expectedly, biogenic emissions contribute the most to total reactivity (attributable dominantly to isoprene), but the furans group is the most reactive with values from 1.24–3.93 s-1. This group contains various furans (furan, 2-methylfuran, m/z 85, and furfural alcohol) wherein m/z 85 is by far the most significant, contributing up to 69 % of the group total. This high m/z 85 presence explains why this group is also the most OH reactive as most furans are largely oxidized by NO3 during this transport timeframe, except m/z 85, which has a long τNO3 but a comparatively shorter τOH. The furan reactivity range is comparable to lab-based values measured in Gilman et al. (2015), which ranged from 1.3–5.5 s-1. Both these studies find lower furan reactivities than lab measurements made in Koss et al. (2018) at an average reactivity of 14.2 s-1, where furans constitute the third highest reactivity group. Aromatics make up the second most reactive group (range of 0.66–2.14 s-1) in this study, with dominant contributions from phenol (39 %), styrene (33 %), and catechol (32 %). Catechol's contribution is likely less than this as other studies have revealed that it shares a significant portion of its mass peak with 5-methyl furfural (Stockwell et al., 2015; Koss et al., 2018). Despite their high NO3 reactivity, phenolic compounds still dominate the overall OH reactivity contributions in this category. These compounds appear across other studies as primary contributors to OH reactivity (Gilman et al., 2015; Hatch et al., 2017; Koss et al., 2018; Sekimoto et al., 2018; Decker et al., 2019; Liang et al., 2022). Alkenes (range of 0.86–1.83 s-1) are on par with aromatics, for which their reactivity is largely attributable to propene and butene, followed finally by non-aromatic oxygenates (range of 0.28–1.87 s-1), which contain compounds like methanol, acetaldehyde, and acetic acid. The comparably low reactivity from this group is unexpected as other studies have shown that the dominant contributions to reactivity come from this group (Gilman et al., 2015; Koss et al., 2018; Liang et al., 2022).

EFs were derived for a total of 15 trace gas species via measurements from a PTR-ToF-MS and an FTIR spectrometer, the resulting OH reactivity of the transported plume quantified, and O3 and NO2 time series investigated. The COALA-2020 ground-based field campaign opportunistically sampled a sustained biomass burning plume from 3–4 February 2020 during the 2019–2020 wildfire season in New South Wales, Australia. We determined via HYSPLIT trajectories that the most likely pathway traveled by the plume was from a distance ranging from ∼ 230–375 km south from fires along the temperate forests of the east coast with contributions from more inland fires near Canberra, Australia. This plume lofted to an altitude of 500 m a.g.l. as it passed over active fires ∼ 8 h out from the field site, before descending to 10 m a.g.l. while traveling over the ocean and reaching the site at 17:30 LT. All data used in the derivation of EFs were limited from sunset on 3 February to sunrise on 4 February as this period showed the greatest enhancements of reactive BB tracers like furan. Through visual inspection, we partitioned this plume event into four portions and calculated and averaged the individual ERs. We used two age marker ratios derived from furan radical oxidation to determine the freshest portion of the plume and found that ERs from this portion corresponded well with the averaged ERs (within 1σ). Using EFs from the entire evening allowed for the inclusion of three more VOC EFs into this analysis which, for the freshest portion of the plume, did not meet the selection criteria for ERs.

We have further characterized wildfire emissions in Australia's temperate region by providing a more comprehensive suite of biome-averaged VOC EFs. This suite introduces new EFs for acrolein, methyl propanoate, methyl methacrylate, maleic anhydride, benzaldehyde, and creosol. Of particular note is acrolein, which has been shown to be a gas-phase variable posing significant harm to human health (O'Dell et al., 2020; Simmons et al., 2022). When compared with values reported from two Australian studies located in the same or nearby temperate forests, we find mixed agreement with results from Guérette et al. (2018), as only two values are captured within our EF variability, with acetonitrile differing by a factor of ∼ 4.5 and MVK + MACR differing by a factor of ∼ 6. However, two compounds are within the range of variability for Lawson et al. (2015) and two others are well within a factor of 2, which indicates reasonable agreement. Furthermore, comparison with two recent US studies that report data on analogous temperate zones, as well as one report covering global temperate regions, show generally good agreement for 9 of the 15 compounds, with several others within a factor of 2, indicating very good agreement. This closer agreement with these studies, as well as that of Lawson et al. (2015), is likely due to the measurement approach when deriving EFs as both US-based studies were aircraft campaigns, and the Australia-based study intercepted a transported plume much like this work. Guérette et al. (2018) sampled controlled burns on a ground campaign virtually at the emission source. This indicates that variability previously ascribed to differing fuel types may be overshadowed by sampling approach and that comprehensive measurements from US-based studies may be useful for studying Australian biomes. Agreement with both Lawson et al. (2015) and the US-based studies indicates that results here are valid for future use in Australian, biome-specific biomass burning studies. Compounding this is the excellent agreement found between EFs in this study and a comparison of two laboratory, US-based, temperate fuel studies, indicating the potential for lab-based results to be similarly applicable. Chemically comprehensive near-source observations of Australian fuel types are needed to evaluate the importance delineating temperate forest EFs in different regions across the globe.

Probing the OH reactivity of the plume revealed that the nighttime conditions, despite the long transport time, transported a quantity that effectively doubled OH reactivity at the COALA-2020 field site, with contributions arising from expected classes of compounds such as furans (most contribution), aromatics (second), and alkenes (third). m/z 85 contributed most significantly of the furans measured, which is due to its long NO3 lifetime but short OH lifetime. Other furans had largely been reacted away before reaching the COALA-2020 field site. Phenol had the largest contribution of the measurable phenolic compounds despite its high NO3 reactivity. Alkenes and aromatics were found, as a group, to have an on par reactivity and, unexpectedly, non-aromatic oxygenates contributed the least.