A number of prevalent atmospheric VOCs contain a terminal alkene moiety, including ethene, propene, isoprene, MACR, MVK, and many of the monoterpenes (e.g., β-pinene, d-limonene, camphene, sabinene, β-ocimene, β-phellandrene, and myrcene). Ozonolysis of such compounds leads to an energy-rich [CH2OO]* Criegee intermediate, along with a carbonyl compound. In the case of ethene (Atkinson et al., 2006):

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The nascent energy-rich Criegee intermediate can then undergo prompt unimolecular decomposition, or collisional stabilization to yield a stabilized Criegee intermediate (SCI):

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The lifetime of stabilized CH2OO is long enough that it can undergo bimolecular reactions with a range of atmospheric compounds (Hasson et al., 2001; Hatakeyama and Akimoto, 1994; Neeb et al., 1996, 1997; Newland et al., 2015; Stone et al., 2014; Su et al., 2014; Vereecken et al., 2012; Welz et al., 2012, 2014). In particular, the reaction with water vapor leads to hydroxymethyl hydroperoxide (HMHP) (Hasson et al., 2001; Neeb et al., 1996, 1997):

. which is known to decompose heterogeneously to HCOOH + H2O (Neeb et al., 1997; Orzechowska and Paulson, 2005). While it is uncertain how readily this occurs in the atmosphere (Lee et al., 1993; Sauer et al., 2001; Valverde-Canossa et al., 2006; Weinstein-Lloyd et al., 1998), photooxidation of HMHP is likely to produce HCOOH in high yield as well (Neeb et al., 1997; Paulot et al., 2011; Stavrakou et al., 2012). For this work we assume prompt conversion of HMHP to HCOOH. This simplification may slightly overestimate HCOOH production from the CH2OO SCI, but an offsetting factor is that there are a number of atmospheric compounds containing terminal alkene groups that are not explicitly represented in the GEOS-Chem chemical scheme.

Estimates of the CH2OO + H2O rate coefficient (kCH2OO+H2O) vary widely. Stone et al. (2014) inferred an upper limit of 9 × 10-17 cm3 molec-1 s-1, with a best estimate of 5.4 × 10-18 cm3 molec-1 s-1 based on relative rate considerations. On the other hand, Newland et al. (2015) derived a value for kCH2OO+H2O of (1.3 ± 0.4) × 10-15 cm3 molec-1 s-1. For the base-case simulations in this work, we employ kCH2OO+H2O=1×10-17 cm3 molec-1 s-1 following version 3.2 of the Master Chemical Mechanism (MCMv3.2) (Jenkin et al., 1997; Saunders et al., 2003). We also carry out separate sensitivity analyses (kCH2OO+H2O=5.4×10-18 and 1.3×10-15 cm3 molec-1 s-1) to test how current uncertainty in this parameter affects our results. Reaction of CH2OO with the water dimer may also be significant in the atmosphere (Chao et al., 2015), and likewise leads to HMHP production (Ryzhkov and Ariya, 2003). However, we do not include such chemistry here, since (as will be seen) the above sensitivity runs already span conditions where CH2OO removal is dominated by reaction with water to form HMHP.

In addition to the sinks above, recent work has found that the CH2OO SCI can be lost by reaction with HCOOH and other carboxylic acids, and by self-reaction. Reactions between SCIs and carboxylic acids are treated as described later (Sect. 2.4). In the case of the CH2OO self-reaction, the kCH2OO+CH2OO rate coefficient was estimated at (4 ± 2) × 10-10 cm3 molec-1 s-1 by Su et al. (2014), which is close to the gas kinetic collision value. However, subsequent work by the same group gives a lower value of (8 ± 4) × 10-11 cm3 molec-1 s-1 (Ting et al., 2014), which agrees with two other recent estimates of (6 ± 2) × 10-11 cm3 molec-1 s-1 (Buras et al., 2014) and (7.4 ± 0.6) × 10-11 cm3 molec-1 s-1 (Chhantyal-Pun et al., 2015). The base-case simulations presented here do not include the CH2OO self-reaction; rather, we include a separate sensitivity run based on the Ting et al. (2014) rate to assess the potential impact of this chemistry on atmospheric HCOOH.

We employ here a stabilized CH2OO yield of 0.37 from ethene ozonolysis (Atkinson et al., 2006). Alam et al. (2011) reported a higher value of 0.54, but more recent work by the same group gives a revised estimate of 0.37 (Newland et al., 2015), in agreement with the IUPAC recommendation. For propene, which is grouped with higher alkenes in the GEOS-Chem mechanism, we use an SCI yield of 12 % for each of the two possible Criegee intermediates (CH2OO and CH3CHOO) based on MCMv3.2 (Jenkin et al., 1997; Saunders et al., 2003). Ozonolysis of isoprene, its oxidation products, and 2-methyl-3-buten-2-ol (MBO), and the associated SCI chemistry, is also implemented following MCMv3.2. Treatment of monoterpenes is described below.

Oxidation of acetylene (or other terminal alkyne) by OH leads to formic acid through formation of a peroxy radical that can then decompose to HCOOH plus an acyl radical, or to a dicarbonyl plus OH (Bohn et al., 1996; Hatakeyama et al., 1986):

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Paulot et al. (2011) found acetylene (C2H2) to be the dominant non-biogenic precursor of formic acid in their simulations. We use in GEOS-Chem branching ratios of 0.364 and 0.636 for the acid and dicarbonyl channels, respectively, in acetylene oxidation (Bohn et al., 1996; Hatakeyama et al., 1986; Jenkin et al., 1997; Saunders et al., 2003).

The HCOOH yield from OH-initiated isoprene oxidation is uncertain. The OH-isoprene oxidation scheme employed here is based on the work of Paulot et al. (2009a, b; 2011), updated to account for peroxy radical isomerization reactions (Crounse et al., 2011, 2012). Pathways leading to HCOOH in this mechanism (aside from the ozonolysis reactions) include photooxidation of glycoaldehyde and hydroxyacetone (Butkovskaya et al., 2006a, b), degradation of isoprene nitrates (Paulot et al., 2009a), and oxidation of isoprene epoxides (Paulot et al., 2009b).

Figure S1 in the Supplement shows the resulting production rate of HCOOH over North America in GEOS-Chem. The total source from isoprene (including ozonolysis plus OH chemistry) over this domain corresponds to an average molar yield of 13 % (2.6 % on a per-carbon basis), and accounts for nearly half of the overall photochemical HCOOH source in the model. Globally, isoprene oxidation accounts for ∼ 45 % of the total HCOOH burden in the GEOS-Chem base-case simulation.

Evidence for direct HCOOH production from glycoaldehyde and hydroxyacetone as reported by Butkovskaya et al. (2006a, b) (and implemented here) is mixed. Orlando et al. (2012) did not find evidence for any significant HCOOH production from these compounds within the range of atmospherically relevant NOx concentrations. Earlier work by Jenkin et al. (1993) on the Cl-atom-initiated oxidation of hydroxyacetone attributed the observed HCOOH production to secondary chemistry that would only be relevant to chamber conditions. Excluding the HCOOH source from glycoaldehyde and hydroxyacetone in the model reduces the global photochemical HCOOH source by over one-third, and (as will be seen) substantially increases the magnitude of the implied missing source.

HCOOH can be produced during OH-initiated oxidation and ozonolysis of monoterpenes (Larsen et al., 2001; Lee et al., 2006a, b; Orlando et al., 2000). The corresponding mechanisms and yields are not well quantified, and the overall effect on atmospheric HCOOH will vary with the mixture of monoterpenes at hand. For the simulations here we employ a single lumped monoterpenes species, with molar HCOOH yields of 15.5 % (OH chemistry) and 7.5 % (ozonolysis) (Paulot et al., 2011). This results in an HCOOH source of 9.8 Gmol over the domain of Fig. S1, 18 % of the model source from isoprene. Globally, monoterpenes account for ∼ 4 % of the HCOOH burden in the base-case simulation.

Andrews et al. (2012) studied the photolysis of C-1 deuterated acetaldehyde (CH3CDO), and observed formation of its isomer CH2DCHO. Modeling of the photo-isomerization implied that upon absorbing a photon, the initially excited acetaldehyde undergoes keto-enol tautomerization (as shown here for the non-deuterated molecule):

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This in turn suggested that a fraction of the enol could be collisionally deactivated to form stable vinyl alcohol. Their best estimate for the vinyl alcohol quantum yield (ϕenol) was 21 ± 4 %. Subsequent work (Clubb et al., 2012) observationally confirmed the formation of vinyl alcohol during acetaldehyde irradiation.

As the photooxidation of vinyl alcohol can lead to formic acid (Archibald et al., 2007; So et al., 2014), we include acetaldehyde tautomerization in GEOS-Chem to gauge its potential importance for atmospheric HCOOH. There are likely to be two offsetting pressure effects on ϕenol: (i) competition between the photo-tautomerization reaction and collisional deactivation of the initially excited acetaldehyde molecule, and (ii) competition between collisional stabilization of the enol and dissociation. Since we lack quantitative constraints on either, we assume here a 21 % quantum yield for enol production, with no pressure (or temperature) dependence. The subsequent photochemical oxidation of vinyl alcohol is then described according to the theoretical rate coefficients derived by So et al. (2014).

However, theory also suggests that HCOOH and other carboxylic acids (as well as other species) can effectively catalyze the reverse tautomerization of vinyl alcohol back to acetaldehyde (da Silva, 2010; Karton, 2014). Including the photo-tautomerization of acetaldehyde as well as the acid-catalyzed reverse reaction (applying the rate derived by da Silva (2010) for both formic and acetic acids), we find that the vinyl alcohol pathway accounts for 15 % of the global HCOOH burden in the model.

As shown in Fig. S2, a consequence of this chemistry is that the efficiency of acetaldehyde tautomerization as a source of atmospheric HCOOH is inversely related to the abundance of HCOOH itself. HCOOH therefore buffers its own production by this mechanism; keto-enol tautomerization can provide a major fraction of the secondary HCOOH source when HCOOH concentrations are low, but it becomes negligible at higher levels of HCOOH.

The rate coefficient for the CH3O2+ OH reaction was recently measured at (2.8 ± 1.4) × 10-10 cm3 molec-1 s-1 (Bossolasco et al., 2014), based on the CH3O2 absorption cross section reported by Faragó et al. (2013). While the 2–3× uncertainty in that cross section (Atkinson and Spillman, 2002; Faragó et al., 2013; Pushkarsky et al., 2000) propagates onto the derived CH3O2+ OH rate, the value derived by Bossolasco et al. (2014) is large enough that OH would represent an important CH3O2 sink in low-NO environments (Fittschen et al., 2014).

The potential implications of this chemistry for HCOOH and other species hinge on the reaction products, which are not known. Archibald et al. (2009) proposed three possible reaction paths – H-atom abstraction to yield a Criegee intermediate, O-atom transfer to yield an alkoxy radical, and nucleophilic substitution to yield an alcohol:

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In the first case, CH2OO can go on to produce HCOOH as discussed earlier.

To test the possible importance of this chemistry for atmospheric HCOOH, we carried out a sensitivity simulation using the reported CH3O2+ OH rate coefficient (Bossolasco et al., 2014) and assuming that the reaction takes place exclusively via H-atom abstraction. The resultant CI is then treated in the same way as in the case of ethene ozonolysis.

Figure 3 shows average vertical profiles of HCOOH and an ensemble of related chemical species as measured over the US Southeast during SENEX. HCOOH mixing ratios average ∼ 2.5 ppb near the surface, decreasing to 0.25–0.7 ppb in the free troposphere. The measured concentrations approach those of HCHO (mean of ∼ 4 ppb near the surface), which is a ubiquitous oxidation product of isoprene and many other VOCs. The high observed HCOOH concentrations indicate that this compound is a major component of the reactive carbon budget, and (if secondary in origin) a central product of VOC oxidation in the atmosphere.

Also shown in Fig. 3 are predicted concentrations from the GEOS-Chem base-case simulation described above. Here and elsewhere, the model has been sampled along the aircraft flight track at the time of measurement. We see that the mean vertical profiles of CO, isoprene, the sum of methyl vinyl ketone and methacrolein (MVK+MACR; both are isoprene oxidation products), formaldehyde (HCHO), total monoterpenes (ΣMONOT), and NOx are all well captured by the model. GEOS-Chem underpredicts CO in the free troposphere, consistent with a low model bias in the CO background (Kim et al., 2013), but otherwise the vertical profiles are in good agreement with observations, in terms of both magnitude and shape.

Conversely, simulated concentrations of HCOOH are dramatically low relative to the aircraft data, averaging only ∼ 1 ppb near the surface. A similar issue is apparent for CH3COOH. In addition to the boundary layer bias, we see for both acids a major model underestimate in the free troposphere: above 600 hPa, observed concentrations for both species average 0.25 ppb or more, whereas those in the model are a factor of 10 less at 10–40 ppt.

The comparisons shown in Fig. 3 do not provide any indication of a major bias in the simulated emissions of isoprene, monoterpenes, or other HCHO precursors that could come close to explaining the observed discrepancy for HCOOH and CH3COOH. Likewise, overly vigorous boundary layer ventilation is untenable as an explanation, based on the accurate model profile shapes for the non-acid species, as well as the fact that both acids are biased low in the model throughout the vertical column. The aircraft measurements clearly demonstrate that some aspect of the model HCOOH budget is seriously in error, and this supports other recent studies based on satellite and in situ measurements (Cady-Pereira et al., 2014; Paulot et al., 2011; Stavrakou et al., 2012). Since the sources of HCOOH are thought to be mainly secondary in nature, this points to a significant gap in our current understanding of hydrocarbon oxidation chemistry. In the next section we apply tracer–tracer relationships measured and simulated during SENEX to shed light on potential missing terms in the HCOOH budget.

Figure 4 shows the simulated HCOOH mixing ratios during SENEX from (i) isoprene oxidation, (ii) other exclusively biogenic sources, and (iii) all other sources, binned and plotted as a function of the observed HCOOH amount. “Other sources” include photochemical production of HCOOH from primary VOCs with anthropogenic or mixed origins (e.g., ethene) as well as direct HCOOH emissions from non-biogenic sources. We see in the figure that when the measured HCOOH concentrations are high, isoprene oxidation is the predominant model source. By itself, this is not clear evidence that the high observed HCOOH concentrations arise from isoprene oxidation, since the modeled HCOOH from isoprene is strongly correlated with that from other biogenic sources (R=0.92). On the other hand, the sole secondary HCOOH source in the model that is purely anthropogenic (acetylene oxidation) has only a weak correlation (R=0.29) with the HCOOH observations.

The strongest correlation between HCOOH and the extensive array of other chemicals observed during SENEX, aside from other carboxylic acids, is with methanol, with R=0.70 for the entire data set and R=0.68 within the planetary boundary layer (PBL; P> 800 hPa). An independent analysis (de Gouw et al., 2014) concluded that methanol variability during SENEX was dominated by emissions from the terrestrial biosphere, and this is consistent with findings from other studies (Hu et al., 2011; Millet et al., 2008b; Stavrakou et al., 2011; Wells et al., 2012, 2014). The observed HCOOH–methanol relationship thus provides an additional indication that biogenic sources are driving the abundance of atmospheric HCOOH over this region.

Figure 5 shows a source attribution of atmospheric HCOOH based on multiple regression of the SENEX observations against concurrent measurements of methanol (as a biogenic tracer) and methyl ethyl ketone (MEK; as an anthropogenic tracer), and with the intercept set to the lowest HCOOH concentrations observed during the campaign (0.01 quantile; 0.1 ppb). MEK exhibits the strongest correlation with HCOOH of any anthropogenic tracer (R=0.42 within the PBL). While MEK is known to have some biogenic sources (de Gouw et al., 1999; Jordan et al., 2009; Kirstine et al., 1998; McKinney et al., 2011), it is thought to be mainly produced from the oxidation of butane and other anthropogenic hydrocarbons (Jenkin et al., 1997; Saunders et al., 2003). As we will see later, observations during SLAQRS in Greater St. Louis imply a significant anthropogenic contribution to atmospheric MEK in that location. We use it here as an anthropogenic tracer; to the degree that MEK is affected by biogenic sources, the associated anthropogenic HCOOH source fraction may be overstated.

We see in Fig. 5 that the resulting regression captures 74 % of the variance in atmospheric HCOOH, and on average attributes 86 % of the observed HCOOH abundance to biogenic sources and less than 15 % to other sources. A bootstrap analysis gives 95 % uncertainty ranges of 82–90 % and 10–18 % for the mean biogenic and other contributions, respectively, while the variance inflation factor (VIF < 5) shows that the regression is not unduly affected by multicollinearity. Here we have transformed (squared) the methanol concentrations to give a linear relationship with HCOOH, using instead the untransformed data yields a smaller biogenic fraction (69 %) but a slightly degraded fit.

The above considerations point to biogenic VOC oxidation (or conceivably direct biotic emissions) as the largest source of atmospheric HCOOH over this part of North America. However, these findings leave room for a comparable per-reaction yield of HCOOH for both biogenic and anthropogenic VOCs, when one considers the emission disparity between the two. Biogenic VOCs have been estimated to account for approximately 88 % of the total (anthropogenic + biogenic) VOC flux from North America in carbon units (Millet et al., 2008a), comparable to the mean biogenic contribution to HCOOH derived above. In fact, similar amounts of HCOOH (∼ 2 ppb) were recently observed during wintertime in the Uintah Basin (Utah, US), where hydrocarbon reactivity is dominated by alkanes and aromatics associated with oil and gas operations, and during summertime in Los Angeles (CA, US), where isoprene and unsaturated anthropogenic compounds make up the major part of the reactivity (Yuan et al., 2015). Production of HCOOH (and likely other carboxylic acids) appears therefore to be a ubiquitous feature of atmospheric hydrocarbon oxidation across a range of precursor types.

Figure 6 shows concentrations of HCOOH and related species measured at the SOAS ground site in Alabama during June and July 2013. This site is located in a mixed deciduous forest 8 km from the small cities of Brent and Centreville (combined population 7700). HCOOH concentrations ranged from near-zero to more than 10 ppb during the SOAS study, with strong diurnal fluctuations. The GEOS-Chem simulation is unable to reproduce the dynamic range seen in the measurements, and exhibits a low bias (on average 3×) that is consistent with the SENEX comparisons above.

We also see in Fig. 6 substantial day-to-day variability in atmospheric HCOOH driven by meteorological shifts. HCOOH concentrations are generally elevated during the warm and sunny conditions that prevailed for much of the period shown in the figure, but drop dramatically during cooler and cloudy days (e.g., 185–189). As shown in Fig. 6, these patterns mirror a number of other biogenic (e.g., methanol) and secondary (e.g., MEK, HNO3) compounds measured at the site. In fact, the strongest HCOOH correlation at SOAS is seen for HNO3 with R=0.78, followed closely by methanol at R=0.74, likely reflecting their common drivers of variability – sunlight-driven production and surface uptake/deposition.

Figure 7 shows mean diurnal cycles for HCOOH and selected other tracers over the entire SOAS campaign. In the case of HCOOH, we see a pronounced morning increase that parallels that of isoprene and appears to slightly precede that of MVK+MACR. Following a peak in the afternoon, HCOOH concentrations drop throughout the evening and night at a rate intermediate between O3 and HNO3. The GEOS-Chem simulation does not reproduce this large diurnal amplitude: HCOOH concentrations are overestimated at night, the prompt morning increase seen in the data is delayed and much too weak, daytime concentrations are underestimated, and the strong evening decline is not captured.

Errors in the model mixing heights may contribute to the above discrepancies, but cannot be the main explanation. We see in Fig. S3 that the GEOS-FP mixing heights for this location are generally too high during the day, and at times appear too low at night. The daytime bias will exacerbate the model HCOOH underestimate at that time; however, the HCOOH discrepancy is too great to be rectified by a 30–50 % mixing height correction. Furthermore, a model underestimate of the nocturnal boundary layer depth should lead to an overprediction of near-surface HCOOH deposition and depletion at night, whereas we see in Fig. 7 a clear underprediction of this sink.

The prompt early-morning HCOOH increase seen during SOAS would seem to implicate direct emissions rather than photochemical production, since the rise occurs simultaneously with that of isoprene. However, we believe this behavior is partly driven by a combination of residual layer entrainment and increasing photochemical production over the course of the morning. The top panel of Fig. 8 shows HCOOH measurements during a nighttime SENEX flight on 2 July 2013 over Alabama and Tennessee. In the vicinity of the SOAS site, HCOOH concentrations aloft are 1.5–2.7 ppb, whereas concentrations at the ground drop to near-zero over the course of the night due to deposition within the shallow surface layer. This elevated residual layer HCOOH is then entrained into the HCOOH-depleted air at the surface as the mixed layer develops after sunrise. We see similar behavior in Fig. 7 for O3 and HNO3. In a further manifestation of this dynamic, SOAS featured several nights with simultaneous enhancements of HCOOH and O3 associated with episodic downmixing of residual layer air.

Figure 8 (bottom panels) also shows mean vertical profiles for HCOOH and other VOCs measured during the same SENEX night flight. We see an inverted HCOOH vertical profile at night, due to surface uptake, that is not present in the model. The same model-measurement disparity is apparent for MVK+MACR, HCHO, and CH3COOH, though to a lesser degree. We thus have a reversal of the vertical gradient of HCOOH and other oxygenated VOCs between the day and night. This progression can be seen in the top panel of Fig. 8: early in the evening (prior to 183.10 UTC), low-altitude flight segments are accompanied by elevated HCOOH, and vice versa. Later in the night, the situation has reversed, with the high altitude segments generally associated with more elevated HCOOH concentrations.

The model's inability to capture the evening HCOOH decline (Fig. 7) and the nocturnal vertical gradient (Fig. 8) implies (i) a substantial underestimate of the HCOOH surface sink, or (ii) overly vigorous model mixing with overlying air during the night (thus replenishing HCOOH from aloft). The former could arise for dynamical (e.g., an overestimate of the aerodynamic and quasi-laminar resistances to deposition) or chemical (e.g., consumption of HCOOH by SCIs or other species) reasons. However, it cannot be due to an underestimate of the surface resistance for HCOOH itself, since as shown in Sect. 4.3 replacing the HCOOH deposition velocity with that for HNO3 does not resolve the model bias in this regard.

Figure 9 compares the modeled and measured nocturnal (19:00–06:00 LST) decay of HCOOH, Ox (O3+ NO2), and MVK+MACR as an average over the SOAS field campaign. Data are plotted on logarithmic axes; the slope then estimates the model : observed ratio of deposition loss frequencies (assuming deposition is the dominant process driving the nighttime decline). We see that the effect of deposition on the ambient nighttime HCOOH concentrations is underestimated in the model by a factor of 4–5. However, a similar bias is apparent for Ox. This suggests a general dynamical bias in the model rather than anything particular to HCOOH, or, perhaps, a chemical sink for both Ox and HCOOH in surface air. A possibility for the latter is terpenoids that consume O3, generating SCI that can then consume or produce HCOOH. Figure 9 also shows that, unlike HCOOH and Ox, the model slope for MVK+MACR is only 30 % lower than observed.

Overall, we see a strong diurnal cycle in HCOOH at the surface, driven by depletion in a shallow surface layer at night, and entrainment of HCOOH-enriched residual layer air plus photochemical production/direct emissions during the day. These dynamics are not captured by the model, but there is inconsistency in model performance for HCOOH and Ox versus MVK+MACR. Improved constraints on surface uptake is a major need to improve our understanding of oxygenated VOCs and other trace gases. If dry deposition of HCOOH is in fact underestimated by the model, the magnitude of its missing source becomes proportionately larger.

The SLAQRS study (August–September 2013) was based in East St. Louis, IL, within the Greater Saint Louis metropolitan area. The edge of the Ozark Plateau, one of the global hotspots for isoprene emission (and referred to as the “isoprene volcano”; Wiedinmyer et al., 2005) lies ∼ 35 km to the south and west of the site. To the north and east lie the predominantly non-isoprene-emitting agricultural landscapes of northern Missouri, southern Illinois, and Iowa. As Fig. 10 shows, the transport regime during the study shifted between northeasterly winds (or stagnant conditions) with low isoprene concentrations, and southwesterly winds that brought heavily isoprene-impacted air masses into the city (up to 8 ppb of isoprene transported from the Ozarks). Because of these regime shifts the site provides a unique opportunity for examining the role of biogenic VOCs in a polluted urban area.

Figure 11 shows the mean diurnal cycle as a function of wind direction for a number of species measured during SLAQRS. We see the highest concentrations of anthropogenic compounds such as CO and benzene when winds are from the northeast (partly reflecting an association with low wind speeds). On the other hand, elevated amounts of isoprene and MVK+MACR are specifically associated with southwesterly winds. Peak concentrations occur at night because of rapid daytime photooxidation during transit from the Ozarks.

Also plotted in Fig. 11 are HCOOH and CH3COOH. In both cases we see high concentrations (several ppb) from all sectors, but the highest amounts clearly occur with the southwesterly winds that also bring elevated isoprene and other biogenic oxidation products. HCOOH and CH3COOH are longer lived than isoprene and MVK+MACR and are not depleted to the same degree during transport; concentrations thus typically peak in the late afternoon rather than at night.

The hottest conditions during SLAQRS occurred with southwesterly winds, raising the question of whether the above HCOOH and CH3COOH enhancements merely reflect accelerated chemistry at high temperatures, or a correlating dynamical effect (e.g., stagnation) rather than a biogenic origin. An examination of two other compounds with a substantial (acetone) to dominant (MEK) secondary anthropogenic source, and comparable photochemical lifetimes to HCOOH and CH3COOH (> 1 day at OH = 107 molec cm-3), reveals that this is not the case. While we do see higher amounts of acetone and MEK with southwesterly winds (Fig. 11), the diurnal cycle is strikingly different than HCOOH and CH3COOH. Here, the concentrations peak following the morning and evening rush hours along with CO and toluene (Fig. S4), rather than in the late afternoon.

The SLAQRS data set is thus consistent with SENEX and SOAS in pointing towards a major biogenic source of formic and acetic acids. However, while the highest ambient levels are clearly linked to biogenic sources, concentrations of several ppb are seen even when isoprene is low. This is consistent with other measurements in urban areas (e.g., Le Breton et al., 2012; Veres et al., 2011) and in an oil and gas producing area (Yuan et al., 2015). The overall indication is of a ubiquitous chemical source of HCOOH (and likely other carboxylic acids) across a range of precursors. Since biogenic emissions dominate the reactive carbon budget, they would then also provide the bulk of the precursor material for HCOOH and related compounds.