3 Results
3.1. Statistics of the OXL:SO42- Ratio
Across multiple environments (Fig. 1), we observe similarities in the
range of the OXL:SO42- ratio (i.e.,
slope) across campaigns except for CAMP2Ex (discussed
in Section 3.2). A combined plot of all campaigns suggests a common
range of OXL:SO42- across different
environments (Fig. S1). Visually, the range in
OXL:SO42- (Fig. S1) decreases with
increasing concentrations, perhaps from a clearer signal of aqueous
processing at higher concentrations.
Bootstrapping across all campaigns reveals a stable median
OXL:SO42- of 0.0217 (R = 0.76; N =
2948) (details in Table S1) with 95% confidence interval bounds (0.0154
– 0.0296) indicating a relative uncertainty range of
~±30% about the median. The bootstrapped statistics are
supported by averaging the OXL:SO42-slopes between campaigns in Fig. 1 (mean: 0.0184, standard deviation:
0.007, median absolute deviation (MAD): 0.004), which, similar to our
bootstrapping method, weights all campaigns equally and removes the
statistical bias towards larger datasets. The bootstrapped 95%
confidence interval of our observed
OXL:SO42- (0.0154 – 0.0296) is in
excellent agreement with the ratio of yields between aqueous SOA (0.008
– 0.033; Ervens et al., 2011) and
SO42- (approximately unity),
corroborating the hypothesis of a general range in
OXL:SO42-. Numerous studies spanning a
diverse set of environments have reported
OXL:SO42- values (Table S2) with
several falling within our bootstrapped range.
Cumulative probability functions (CDFs) were plotted to more easily
compare OXL:SO42- between campaigns
(Fig. S2). As point-by-point ratios are sensitive to background levels
of OXL and SO42-, we plotted CDFs of
their enhancement ratio (ΔOXL/ΔSO4) where values were subtracted by
their 10th percentile to approximate background levels
per campaign. The resulting CDFs showed similar curves between multiple
campaigns and revealed that approximately 20% of point-by-point
OXL:SO42- values fall within our
bootstrapped 95% confidence interval (0.0154 – 0.0296) while
~50% of OXL:SO42-values fall within 0.010 – 0.050. In comparison with the linear
regression slope, point-to-point ratios are more susceptible to
differences in background, resulting in differences in agreement with
our 95% confidence interval (e.g., CHECSM). This is a consequence of
the point-by-point calculation: although the dataset as a whole may have
a mean slope within our confidence interval, there may still be
variability in the OXL:SO42- ratios of
individual points. Thus, as the 10th percentile merely
accounts for campaign backgrounds, the linear regression slopes (Fig. 1)
may better handle different environments by implicitly accounting for
individual background levels via non-zero intercepts.
Surface OXL:SO42- values from CHECSM
agree with the bootstrapped 95% confidence interval for non-BB samples
for PM18 (0.0264; Fig. 1g) and PM1(0.0196) modes (R = 0.73 for both). Size-resolved data show that this
agreement is greatest between 0.32–1 μm (Fig. S3a), where OXL and
SO42- masses mostly reside (Cruz et
al., 2019). An increase in supermicrometer
OXL:SO42- (Fig. S3a) suggests the
enhancement of OXL via gas-particle partitioning of OXL and/or its
precursors onto coarse particles as documented for the CHECSM region
(Stahl et al., 2020b; Stahl et al., 2021). These results suggest the
ratio may be applicable to the mixed layer for submicrometer particles.
AToM provides insight into the
OXL:SO42- ratio over remote marine
environments in both hemispheres. The Pacific and Atlantic Oceans
(< 3 km AGL) have a combined
OXL:SO42- ratio of 0.0207 (R = 0.51)
(Fig. 1f). Separately, the Pacific and Atlantic have ratios of 0.0180 (R
= 0.36) and 0.0251 (R = 0.72), respectively, remarkably similar to other
environments (Fig. 1). Across altitudes (Fig. S4),
OXL:SO42- values for the Pacific
between 0 – 7.5 km AGL are within our 95% confidence interval (Fig.
S4a) but only near-surface Atlantic samples fall within our confidence
interval (Fig. S4c), possibly due to OXL and/or its precursors
undergoing gas-particle partitioning onto Saharan dust.
Variability in OXL:SO42- across
campaigns was most evident in MASE-II (Fig. 1d) and
CAMP2Ex (Fig. 1h), which had instances of very low
OXL:SO42-, attributable to (1) fresher
plumes that have not had time to form OXL (Wonaschuetz et al., 2012),
(2) the degradation of OXL into CO2 (Zhou et al., 2020),
(3) the formation of OXL-metal complexes (Sorooshian et al., 2013; Tao
& Murphy, 2019), and (4) the presence of high
SO42- backgrounds. Correlation
coefficients below 0.50 (Fig. 1) signify the presence of confounding
sources, an expected result given the diversity of environments
analyzed. Seasonal factors may also influence the ratio (Tao & Murphy,
2019). Variability between campaigns (Fig. 1) may be suggestive of
SO42- from cloud-free photochemistry
and gas-phase oxidation (Ervens, 2015), which are important sources of
uncertainty when using the OXL:SO42-ratio to assess aqueous processing, as our proposed range implies that
SO42- is mainly from aqueous
processing.
The main utility of this ratio is to gauge relative rather than absolute
extents of aqueous processing between air masses via a comparison of
inferred OXL. Considering the differences between OXL and
SO42- in terms of their precursors,
formation mechanisms, and sinks, the consistency of the
OXL:SO42- ratio across multiple
environments implies a convergence towards a fairly narrow range, which
is assisted in part by the large sample sizes used in this study.