Total organic carbon and the contribution from speciated organics in cloud water: airborne data analysis from the CAMP2Ex field campaign

Abstract

This work focuses on total organic carbon (TOC) and contributing species in cloud water over Southeast Asia using a rare airborne dataset collected during NASA's Cloud, Aerosol and Monsoon Processes Philippines Experiment (CAMP2Ex), in which a wide variety of maritime clouds were studied, including cumulus congestus, altocumulus, altostratus, and cumulus. Knowledge of TOC masses and their contributing species is needed for improved modeling of cloud processing of organics and to understand how aerosols and gases impact and are impacted by clouds. This work relies on 159 samples collected with an axial cyclone cloud-water collector at altitudes of 0.2–6.8 km that had sufficient volume for both TOC and speciated organic composition analysis. Species included monocarboxylic acids (glycolate, acetate, formate, and pyruvate), dicarboxylic acids (glutarate, adipate, succinate, maleate, and oxalate), methanesulfonic acid (MSA), and dimethylamine (DMA). TOC values range between 0.018 and 13.66 ppm C with a mean of 0.902 ppm C. The highest TOC values are observed below 2 km with a general reduction aloft. An exception is samples impacted by biomass burning for which TOC remains enhanced at altitudes as high as 6.5 km (7.048 ppm C). Estimated total organic matter derived from TOC contributes a mean of 30.7 % to total measured mass (inorganics + organics). Speciated organics contribute (on a carbon mass basis) an average of 30.0 % to TOC in the study region and account for an average of 10.3 % to total measured mass.
The order of the average contribution of species to TOC, in decreasing contribution of carbon mass, is as follows (±1 standard deviation): acetate (14.7 ± 20.5 %), formate (5.4 ± 9.3 %), oxalate (2.8 ± 4.3 %), DMA (1.7 ± 6.3 %), succinate (1.6 ± 2.4 %), pyruvate (1.3 ± 4.5 %), glycolate (1.3 ± 3.7 %), adipate (1.0 ± 3.6 %), MSA (0.1 ± 0.1 %), glutarate (0.1 ± 0.2 %), and maleate (< 0.1 ± 0.1 %). Approximately 70 % of TOC remains unaccounted for, highlighting the complex nature of organics in the study region; in samples collected in biomass burning plumes, up to 95.6 % of TOC mass is unaccounted for based on the species detected. Consistent with other regions, monocarboxylic acids dominate the speciated organic mass (∼ 75 %) and are about 4 times more abundant than dicarboxylic acids.
Samples are categorized into four cases based on back-trajectory history, revealing source-independent similarity between the bulk contributions of monocarboxylic and dicarboxylic acids to TOC (16.03 %–23.66 % and 3.70 %–8.75 %, respectively). Furthermore, acetate, formate, succinate, glutarate, pyruvate, oxalate, and MSA are especially enhanced during biomass burning periods, which is attributed to peat emissions transported from Sumatra and Borneo. Lastly, dust (Ca2+) and sea salt (Na+/Cl-) tracers exhibit strong correlations with speciated organics, supporting how coarse aerosol surfaces interact with these water-soluble organics.

Full text

Atmos. Chem. Phys., 21, 14109–14129, 2021
https://doi.org/10.5194/acp-21-14109-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Total organic carbon and the contribution from speciated organics
in cloud water: airborne data analysis from the
CAMP2Ex field campaign
Connor Stahl1, Ewan Crosbie2,3, Paola Angela Bañaga4,5, Grace Betito4, Rachel A. Braun1, Zenn Marie Cainglet4,5 ,
Maria Obiminda Cambaliza4,5, Melliza Templonuevo Cruz4,6, Julie Mae Dado7, Miguel Ricardo A. Hilario4,8,
Gabrielle Frances Leung4,9, Alexander B. MacDonald1, Angela Monina Magnaye7, Jeffrey Reid10, Claire Robinson2,3 ,
Michael A. Shook2, James Bernard Simpas4,5, Shane Marie Visaga5,7, Edward Winstead2,3, Luke Ziemba2, and
Armin Sorooshian1,8
1Department of Chemical and Environmental Engineering, University of Arizona, Tucson, Arizona 85721, USA
2NASA Langley Research Center, Hampton, Virginia 23666, USA
3Science Systems and Applications, Inc., Hampton, Virginia 23666, USA
4Air Quality Dynamics-Instrumentation & Technology Development Laboratory, Manila Observatory,
Quezon City 1108, Philippines
5Department of Physics, School of Science and Engineering, Ateneo de Manila University, Quezon City 1108, Philippines
6Institute of Environmental Science and Meteorology, University of the Philippines, Diliman, Quezon City 1101, Philippines
7Regional Climate Systems Laboratory, Manila Observatory, Quezon City 1108, Philippines
8Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, Arizona 85721, USA
9Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado 80521, USA
10Marine Meteorology Division, Naval Research Laboratory, Monterey, California 93943, USA
Correspondence: Connor Stahl (cstahl1@email.arizona.edu)
Received: 13 May 2021 – Discussion started: 13 May 2021
Revised: 11 August 2021 – Accepted: 30 August 2021 – Published: 23 September 2021
Abstract. This work focuses on total organic carbon (TOC)
and contributing species in cloud water over Southeast Asia
using a rare airborne dataset collected during NASA’s Cloud,
Aerosol and Monsoon Processes Philippines Experiment
(CAMP2Ex), in which a wide variety of maritime clouds
were studied, including cumulus congestus, altocumulus, al-
tostratus, and cumulus. Knowledge of TOC masses and their
contributing species is needed for improved modeling of
cloud processing of organics and to understand how aerosols
and gases impact and are impacted by clouds. This work re-
lies on 159 samples collected with an axial cyclone cloud-
water collector at altitudes of 0.2–6.8 km that had sufficient
volume for both TOC and speciated organic composition
analysis. Species included monocarboxylic acids (glycolate,
acetate, formate, and pyruvate), dicarboxylic acids (glutarate,
adipate, succinate, maleate, and oxalate), methanesulfonic
acid (MSA), and dimethylamine (DMA). TOC values range
between 0.018 and 13.66 ppm C with a mean of 0.902 ppm
C. The highest TOC values are observed below 2 km with
a general reduction aloft. An exception is samples impacted
by biomass burning for which TOC remains enhanced at al-
titudes as high as 6.5 km (7.048 ppm C). Estimated total or-
ganic matter derived from TOC contributes a mean of 30.7 %
to total measured mass (inorganics +organics). Speciated
organics contribute (on a carbon mass basis) an average of
30.0 % to TOC in the study region and account for an aver-
age of 10.3 % to total measured mass.
The order of the average contribution of species to TOC,
in decreasing contribution of carbon mass, is as follows
(±1 standard deviation): acetate (14.7 ±20.5 %), formate
(5.4 ±9.3 %), oxalate (2.8 ±4.3 %), DMA (1.7 ±6.3 %),
succinate (1.6 ±2.4 %), pyruvate (1.3 ±4.5 %), glycolate
(1.3 ±3.7 %), adipate (1.0 ±3.6 %), MSA (0.1 ±0.1 %),
glutarate (0.1 ±0.2 %), and maleate (<0.1 ±0.1 %). Ap-
Published by Copernicus Publications on behalf of the European Geosciences Union.

14110 C. Stahl et al.: Total organic carbon and the contribution from speciated organics in cloud water
proximately 70 % of TOC remains unaccounted for, high-
lighting the complex nature of organics in the study region; in
samples collected in biomass burning plumes, up to 95.6 %
of TOC mass is unaccounted for based on the species de-
tected. Consistent with other regions, monocarboxylic acids
dominate the speciated organic mass (∼75 %) and are about
4 times more abundant than dicarboxylic acids.
Samples are categorized into four cases based on back-
trajectory history, revealing source-independent similarity
between the bulk contributions of monocarboxylic and dicar-
boxylic acids to TOC (16.03 %–23.66% and 3.70 %–8.75 %,
respectively). Furthermore, acetate, formate, succinate, glu-
tarate, pyruvate, oxalate, and MSA are especially enhanced
during biomass burning periods, which is attributed to peat
emissions transported from Sumatra and Borneo. Lastly, dust
(Ca2+) and sea salt (Na+/Cl−) tracers exhibit strong correla-
tions with speciated organics, supporting how coarse aerosol
surfaces interact with these water-soluble organics.
1 Introduction
The last 2 decades have witnessed an acceleration in research
to unravel the nature of the organic fraction of airborne par-
ticles, including speciation (Hallquist et al., 2009; Kanaki-
dou et al., 2005), with implications for how particles im-
pact air quality, public health, and the planet’s energy bal-
ance. However, there has been much less progress on or-
ganic research into cloud droplets, owing largely to the in-
accessibility of clouds compared with particles that can be
measured more easily near the surface. Analyzing organic
matter in cloud water will lead to a better understanding of
secondary aerosol formation and the nature of cloud con-
densation nuclei (CCN) that form droplets. The interaction
of aerosol particles and clouds constitutes the largest un-
certainty in estimating total anthropogenic radiative forcing
(IPCC, 2013), which motivates the use of cloud composition
as a tool to learn about these processes (MacDonald et al.,
2020). Characterizing cloud water composition is insightful
for atmospheric chemical processes such as the removal of
gases that would otherwise participate in gas-phase reactions
and for aqueous reactions that yield products without an ef-
ficient gas-phase source (e.g., dicarboxylic acids) (Ervens et
al., 2013). While modeling of sulfate production in clouds is
fairly mature (Barth et al., 2000; Faloona, 2009; Kreidenweis
et al., 2003; Liu et al., 2021), the formation and evolution of
organics in cloud water is much more poorly constrained (Er-
vens, 2015).
Advancing this research requires in situ measurements of
cloud water composition. Among the most common methods
of characterizing the organic fraction of cloud water sam-
ples is total organic carbon (TOC) analysis. Irrespective of
whether studies have been focused on cloud water or fog wa-
ter, most work has shown the following: (i) TOC is enhanced
in air masses with higher anthropogenic influence (Collett
et al., 1998; Deguillaume et al., 2014; Herckes et al., 2013;
Raja et al., 2009); (ii) ∼40 %–85 % of TOC is attributed to
unidentified species (Benedict et al., 2012; Boris et al., 2016,
2018; Herckes et al., 2002; Raja et al., 2008); (iii) organic
acids usually account for 15 % of TOC (Deguillaume et al.,
2014; Gioda et al., 2011; Straub et al., 2007); (iv) mono-
carboxylic acids are more abundant than dicarboxylic acids
(Löflund et al., 2002); and (v) acetic and formic acids are the
most dominant organic acids contributing to TOC (Collett et
al., 2008; Gioda et al., 2011). Most of the aforementioned
studies focused on fog, motivating a closer look at cloud wa-
ter, as solute concentrations depend on the type of aqueous
medium (Fig. 1). More specifically, TOC concentrations are
reported to be higher in fog water relative to rain water (Kim
et al., 2020), whereas cloud water solute concentrations ex-
ceed those in rain water (Decesari et al., 2005; Gioda et al.,
2008).
Southeast Asia is an ideal laboratory to investigate the
nature of TOC and its constituents, as it is impacted by
a multitude of emission sources in an environment with
persistent cloud cover from a variety of cloud types (e.g.,
shallow cumulus and cumulus congestus clouds) (Reid et
al., 2013). The complex meteorology of the region makes
it very difficult to model (Wang et al., 2013; Xian et al.,
2013) but also simultaneously provides a remarkable oppor-
tunity to learn more about how aerosols impact (and are
impacted by) tropical cloud systems. A knowledge gap ex-
ists, as there have been no studies of cloud composition in
this region based on airborne measurements. Analysis of fog
water at Baengnyeong Island in the eastern Yellow Sea re-
vealed that organic acids accounted for 36 %–69 % of TOC
(Boris et al., 2016). The Acid Deposition Monitoring Net-
work in East Asia (https://www.eanet.asia/, last access: 10
August 2021) provides data on wet deposition at surface
sites such as at the Manila Observatory (Ma et al., 2021),
Metropolitan Manila (Metro Manila), Philippines, and is lim-
ited to inorganic ions. Previous studies such as the Seven
South East Asian Studies (7SEAS) (Reid et al., 2013) and the
Cloud, Aerosol and Monsoon Processes Philippines Exper-
iment (CAMP2Ex) weatHEr and CompoSition Monitoring
(CHECSM) were carried out in this region; however, these
campaigns were ground- and ship-based, and focused mainly
on aerosol particles and not cloud composition (Hilario et al.,
2020b; Reid et al., 2015, 2016). Moreover, it should be noted
that there have also been a handful of high-elevation studies
carried out in Southeast Asia examining fog and cloud wa-
ter organic acids (i.e., Decesari et al., 2005; Li et al., 2017;
Mochizuki et al., 2020).
Recent studies in Metro Manila, Philippines, provide the
following results of relevance to this work: (i) a third to a
half of the total aerosol particle mass is often unaccounted
for after considering water-soluble species (inorganic and or-
ganic acid ions and elements) and black carbon (Cruz et al.,
2019; Stahl et al., 2020); (ii) organic acids account for less
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C. Stahl et al.: Total organic carbon and the contribution from speciated organics in cloud water 14111
Figure 1. TOC (or dissolved organic carbon, DOC, if TOC values
were unavailable) concentrations reported for past studies in rela-
tion to this work organized by continent. Bars represent the average
values, and the error bars represent the minimum and maximum
values. The absence of a solid bar means that no average was avail-
able. No error bars means that there was no range given, and “∗”
indicates that the median value was reported rather than an average.
Gray, yellow, and blue bars represent studies looking at fog, clouds,
and rain, respectively. Bars that are outlined in black are studies
that used TOC, and bars outlined in red are studies that used DOC.
The nvalues represent the number of samples used in the study,
and NL means that the number of samples was not listed. Bolded
nvalues denote airborne samples. This figure is similar to Fig. 2
in Herckes et al. (2013) with additional information presented and
organized by continent. The superscript letters used in the figure de-
note the following: a – Boris et al. (2018), b – Collett et al. (1998),
c – Herckes et al. (2002), d – Herckes et al. (2007), e – Straub et
al. (2007), f – Erel et al. (1993), g – Ehrenhauser et al. (2012), h
– Ervens et al. (2013), i – Zhang and Anastasio (2001), j – Raja et
al. (2008), k – Cook et al. (2017), l – Hutchings et al. (2008), m –
Straub et al. (2012), n – Straub (2017), o – Anastasio et al. (1994), p
– Gioda et al. (2011), q – Gioda et al. (2008), r – Reyes-Rodríguez et
al. (2009), s – Benedict et al. (2012), t – Deguillaume et al. (2014),
u – Capel et al. (1990), v – Gelencser et al. (2000), w – Hadi et
al. (1995), x – Boris et al. (2016), y – Decesari et al. (2005), z –
Wang et al. (2011), aa – Shen (2011), and ab – Kim et al. (2020).
than 1 % of total aerosol mass, with oxalate being the most
abundant acid (Stahl et al., 2020); (iii) organic acid con-
centrations are more enhanced during biomass burning pe-
riods (Hilario et al., 2020a), especially succinate and oxalate
(Braun et al., 2020; Stahl et al., 2020); and (iv) wet depo-
sition samples clearly show the influence of biomass burn-
ing tracer species on cloud composition (Ma et al., 2021).
Based on these points, we test two hypotheses: (i) the rela-
tive contribution of organic acids to TOC will exceed what
was observed in the surface layer over Metro Manila ow-
ing to more aged air masses aloft compared with the surface
layer in Metro Manila, which is exposed to fresher emissions;
and (ii) clouds impacted by biomass burning emissions will
exhibit chemical profiles shifted to higher TOC concentra-
tions and with a greater portion of that TOC accounted for
by organic acids. To address these hypotheses in addition to
characterizing the organic fraction of cloud water, we uti-
lized a rich set of cloud water samples collected around the
Philippines during CAMP2Ex between August and October
in 2019. The subsequent results and discussion focus on TOC
concentrations in addition to the relative contribution and in-
terrelationships between a suite of organic species (organic
acids, methanesulfonic acid, and dimethylamine) both spa-
tially and as a function of altitude and air mass source origin.
A unique aspect of this dataset is the large sample number
with both TOC and speciated organic acid information from
an airborne platform.
2 Methods
2.1 Study overview
A total of 159 cloud water samples were collected by the
NASA P-3B Orion aircraft across 19 research flights (RF;
23 August–5 October 2019) during CAMP2Ex and were
measured for ions, pH, and TOC. Flights were based out of
Clark International Airport (15.189◦N, 120.547◦E) and ex-
tended to regions around the island of Luzon (Fig. 2). Cloud
water samples were collected over a wide range of altitudes
ranging from 0.2 to 6.8 km.
2.2 Cloud water collection and handling
Samples were collected using an axial cyclone cloud-water
collector (AC3), (Crosbie et al., 2018), which efficiently
(>60 % collection efficiency) collects cloud droplets with di-
ameters >20 µm. The size dependence of the collection ef-
ficiency may influence the measured properties of the bulk
cloud water in cases where there is a strong size depen-
dence in the droplet composition. Sample water evapora-
tion was identified to affect low-liquid-water-content envi-
ronments and may increase aqueous concentrations. For this
study, the pipe position was set to position 10, as described
in Crosbie et al. (2018), and mounted to the fuselage pylon
approximately 300 mm from the skin. The AC3 has a shut-
ter attached to a servo motor, allowing the collector to be
closed when not in a cloud to prevent contamination. Sam-
ples were collected for between 10 s and 10 min depending
on cloud availability and liquid water content (i.e., shorter
times possible with higher liquid water content). Cloud water
was collected in prewashed 15 mL plastic conical vials. Due
to thorough prewashing of the plastic conical vials, leaching
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14112 C. Stahl et al.: Total organic carbon and the contribution from speciated organics in cloud water
Figure 2. Map of the sample region. The stars represent the mid-
point of the cloud water samples where total organic carbon (TOC)
was measured, and they are colored by TOC on a logarithmic scale.
of organics into samples was negligible. Additional labora-
tory tests also indicated that there was no appreciable evi-
dence that organics were adsorbing to the walls of the con-
ical vials. Before each flight, the collector was flushed with
∼1 L of ultra-purified Milli-Q water (18.2 M.cm) prior to
obtaining two blank samples. Blanks, which were similarly
flushed prior to collection, were also collected post-flight.
During flight, samples were collected and stored in a cooler
containing a sufficient number of ice packs to reduce possi-
ble decomposition. After flights, samples were immediately
taken to an on-site laboratory where sample volumes were
recorded and analyzed for ionic composition, TOC, and pH.
A background was subtracted from the samples based on the
bottom 10th percentile of all blanks collected during the cam-
paign (both pre- and post-flight). The 10th percentile of the
blanks was used instead of the mean, as it is a compromise
between removing the influence of background contamina-
tion and conserving data points. Excess samples were stored
in a refrigerator for future analyses that are outside the scope
of this study.
2.3 Cloud water analysis
2.3.1 Ion chromatography
Cloud water was speciated using ion chromatography (IC;
Dionex ICS-2100) immediately after each flight to reduce the
possibility of sample degradation. Measured anionic species
of interest were glycolate, acetate, formate, methanesulfonic
acid, pyruvate, glutarate, adipate, succinate, maleate, oxalate,
Cl−, NO−
2, Br−, NO−
3, and SO2−
4. Measured cations were
Na+, NH+
4, K+, dimethylamine (DMA), Mg2+, and Ca2+.
A 23 min instrument method with a 2 min equilibration pe-
riod was used for both anion and cation columns, yield-
ing a 25 min sampling period per sample. The instrument
flow rate was 0.4 mL min−1. The anions were measured us-
ing a Dionex IonPac AS11-HC 2 mm ×250 mm column, a
Dionex AERS 500e suppressor, and potassium hydroxide as
the eluent. The cations were measured using a Dionex IonPac
CS12A 2 ×250 mm column, a Dionex CERS 500e suppres-
sor, and using methanesulfonic acid (MSA) as the eluent. The
instrument methods used for analysis are as follows: (i) for
anions, the eluent concentration started at 1 mM, ramped up
to 4 mM between 0 and 10 min, ramped up to 6 mM be-
tween 10 and 11 min, and finally ramped up to 7 mM between
11 and 23 min using a suppressor current of 8 mA; (ii) for
cations, the eluent concentration started at 5 mM and re-
mained isocratic between 0 and 10 min, ramped up to 18mM
between 10 and 12 min, and finally remained isocratic at
18 mM between 12 and 23 min using a suppressor current
of 22 mA. The limits of detection (LODs) for these species
can be found in Table 1 and were calculated using 3Sab−1,
where Sais the standard deviation of the response, and bis
the slope of the calibration curve for that species.
2.3.2 Total organic carbon and pH
Total organic carbon (TOC) was measured using a Sievers
800 Turbo TOC analyzer. Sample aliquots were diluted to
obtain the minimum volume needed by the instrument. The
TOC analyzer was operated in turbo mode, and TOC val-
ues were averaged over a stable concentration period. Milli-
Q water was used as an internal reference, and calibrations
were performed before and after each batch of samples was
analyzed (i.e., one batch approximately every three to four
flights) using a range of different concentrations from an ox-
alate standard solution. A volume of approximately 10 mL
was used for each measurement, and Milli-Q water was used
intermittently to flush the instrument between each sample.
The pH of the cloud water samples was measured using an
Orion Star™ A211 pH meter with an Orion™ 8103BNUWP
ROSS Ultra™ pH electrode (precision of 0.01). A two-point
calibration (pH =4 and pH =7) was performed at the be-
ginning of the analysis of a particular flight’s set of samples.
2.3.3 Units
While many studies report concentrations in terms of air-
equivalent concentrations, we instead use the native liquid-
phase concentrations. Aqueous concentrations of TOC and
individual molecular components are reported in units of
parts per billion by mass (ppb). TOC concentrations are spe-
cific to the mass of carbon atoms only, whereas molecules
measured by IC correspond to the specific mass of the species
(unless noted otherwise). TOC was converted to total organic
matter (TOM) via multiplication by 1.8 (Zhang et al., 2005).
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C. Stahl et al.: Total organic carbon and the contribution from speciated organics in cloud water 14113
Table 1. Mass concentration limits of detection (LODs), minimum, maximum, mean, 1 standard deviation, and median values (ppb; left), in
addition to the mass fraction (%; right) for the 159 CAMP2Ex cloud water samples with TOC data; note that mass fraction values depend on
the C mass of each organic species shown. Total measured mass is defined as the sum of TOM, Na+, NH+
4, K+, Mg2+, Ca2+, Cl−, NO−
2,
Br−, NO−
3, and SO2−
4. The abbreviations used in the table are as follows: MCAs – monocarboxylic acids, DCAs – dicarboxylic acids, MSA
– methanesulfonic acid, DMA – dimethylamine, MO – measured organics, TOM – total organic matter, and DL – detection limit.
LOD Concentration (ppb) Mass fraction (%)
Min Max Median Mean SD Min Max Median Mean SD
Glycolate 98.76 <DL 224.8 10.65 13.49 20.34 0.0 35.0 0.6 1.3 3.7
Acetate 6.376 <DL 3926 159.4 251.4 409.9 0.0 100.0 10.5 14.7 20.5
Formate 19.77 2.095 3819 66.58 188.5 432.5 0.2 100.0 3.8 5.4 9.3
Pyruvate 5.452 <DL 296.9 5.359 24.35 41.28 0.0 56.1 0.5 1.3 4.5
MCAs – 13.40 8042 253.4 477.8 857.8 0.6 100.0 16.9 22.6 33.9
Glutarate 43.70 <DL 258.7 <DL 6.824 27.32 0.0 1.0 0.0 0.1 0.2
Adipate 39.21 <DL 71.45 2.977 5.331 8.306 0.0 43.7 0.4 1.0 3.6
Succinate 38.64 <DL 1372 <DL 55.23 137.7 0.0 9.3 0.0 1.6 2.4
Maleate 14.81 <DL 14.73 <DL 0.6880 2.310 0.0 0.8 0.0 0.0 0.1
Oxalate 55.23 <DL 1135 38.64 95.65 148.2 0.0 43.9 1.7 2.8 4.3
DCAs – 1.479 2766 61.40 163.7 295.3 0.1 69.8 3.3 5.5 7.5
MSA 88.01 <DL 24.79 3.9 5.107 5.313 0.0 0.9 0.1 0.1 0.1
DMA 56.97 <DL 183.8 <DL 11.16 32.41 0.0 45.3 0.0 1.7 6.3
MO – 29.46 10820 334.3 657.7 1125 1.5 100.0 23.8 30.0 41.2
TOC 0.05 18.00 13 660 546 902 1435 ↑Relative to TOC (%)
Inorganic/TOM – 0.05 90.29 3.31 5.82 8.56 ↓Relative to total measured
pH – 3.79 5.93 5.19 5.04 0.51 concentrations (%)
MO – – – – – – 0.8 57.6 7.2 10.3 9.2
TOM – 32.40 24 590 983 1624 2584 1.1 95.1 23.2 30.7 24.5
Inorganic – 25.99 117 900 3894 8651 13 645 4.9 98.9 76.8 69.3 24.5
Na 16.62 <DL 29 280 609 1650 3192 0.0 26.6 9.5 10.0 7.8
NH4176.8 <DL 8099 427 804 1010 0.0 68.1 7.2 11.2 13.2
K 142.4 <DL 1211 21.40 75.35 144 0.0 21.8 0.5 0.8 2.0
Mg 46.20 <DL 3701 57.87 182 379 0.0 4.0 1.0 1.1 0.9
Ca 74.81 <DL 1951 118 201 277 0.0 25.2 1.6 3.5 4.6
Cl 76.59 <DL 38 200 908 2451 4438 0.0 42.7 15.3 16.0 11.7
NO246.24 <DL 16.31 <DL 1.551 3.304 0.0 0.4 0.0 0.0 0.1
Br 7.817 <DL 44.05 1.398 4.081 7.120 0.0 0.2 0.0 0.0 0.0
NO317.33 <DL 26 560 572 1488 2925 0.0 43.4 10.4 12.6 8.2
SO4414.7 2.318 15 680 868 1795 2495 0.4 34.9 14.1 14.0 8.5
The choice to focus on aqueous-equivalent rather than
air-equivalent concentrations was made for various reasons.
First, our analysis focuses heavily on relative amounts of
species that were unaffected by multiplying native aqueous
units by cloud liquid water content. Second, the definition
of liquid water content applied by studies can vary widely
based on the lower and upper bound of what is considered a
droplet. Third, relationships between solute concentrations in
cloud water and liquid water content, anticipated from nucle-
ation scavenging, are ineffective when gases like acetic and
formic acids absorb directly into droplets rather than having
been part of the initial CCN activating into droplets (Khare
et al., 1999; Marinoni et al., 2004). Lastly, many studies of
cloud water composition that our results can be contrasted
with also use liquid units. The primary liquid units reported
for cloud water concentrations are parts per million by vol-
ume (ppm) and ppb. However, it should be noted that species
concentrations in cloud water can be high simply due to the
liquid water content being low, or inversely, the concentra-
tions can be low due to being diluted by high liquid water
content.
2.4 Aerosol composition
To complement the cloud water composition results, we use
aerosol composition results from a high-resolution time-of-
flight aerosol mass spectrometer (AMS; Aerodyne, Inc.),
which reports non-refractory composition for the submi-
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14114 C. Stahl et al.: Total organic carbon and the contribution from speciated organics in cloud water
crometer range (DeCarlo et al., 2006). As summarized by
Hilario et al. (2021), the AMS deployed in CAMP2Ex func-
tioned in 1 Hz Fast-MS mode with data averaged to a 30 s
time resolution with the lower limit of detection (units
of µg m−3) as follows for the measured species: organic
(0.169), NH+
4(0.169), SO2−
4(0.039), NO−
3(0.035), and Cl−
(0.036). Negative mass concentrations were recorded ow-
ing to the difference method used with the limits of detec-
tion. These negative values were included in the analyses to
avoid positive biases but were interpreted as zero concen-
trations. We also use data specifically for the mass spec-
tral marker representative of acid-like oxygenated organic
species (m/z 44 =COO+) (Aiken et al., 2008) and its mass
relative to total organic mass (f44). AMS data were omitted
from the analysis if the total mass of all detected species was
<0.5 µg m−3. By convention for airborne sampling, AMS
data are reported at standard temperature and pressure (STP;
273 K, 1013 hPa).
AMS data were reported separately for cloud-free and
cloudy conditions owing to the use of a counterflow virtual
impactor (CVI) inlet (Brechtel Manufacturing Inc.) (Shingler
et al., 2012) in clouds to isolate and dry droplets, leaving the
residual particles for sampling by the AMS. Cloud-free data
involve sampling with a separate inlet designed by the Uni-
versity of Hawaii (McNaughton et al., 2007). For cloud-free
AMS results, data were selected 60 s before and after each
cloud water sample’s start and end time, respectively, when
the aircraft was not in cloud. AMS–CVI data were reported
for data collected within the period of cloud water collection.
It should be noted that cloud-free AMS data are missing for
some cloud water samples when the CVI was still in use for
the 60 s before and after a sample’s start and end time, re-
spectively.
2.5 HYSPLIT
Air mass origination was determined using 5 d back trajecto-
ries from the National Oceanic and Atmospheric Administra-
tion (NOAA) Hybrid Single Particle Lagrangian Integrated
Trajectory (HYSPLIT) model (Rolph et al., 2017; Stein et
al., 2015). Trajectories were generated at 1 min temporal res-
olution with meteorological inputs from the Global Fore-
cast System (GFS) reanalysis with a horizontal resolution of
0.25◦×0.25◦using the “model vertical velocity” method.
2.6 NAAPS
The Navy Aerosol Analysis and Prediction System (NAAPS)
global aerosol model was implemented to assist in identi-
fying biomass burning cases (Lynch et al., 2016) (https://
www.nrlmry.navy.mil/aerosol/, last access: 10 August 2021).
NAAPS relies on global meteorological fields from the
Navy Global Environmental Model (NAVGEM) (Hogan and
Brody, 1993; Hogan and Rosmond, 1991) that analyzes and
forecasts a 1◦×1◦grid with 6 h intervals and 24 vertical lev-
els. In terms of identifying biomass burning cases, surface
smoke concentrations were examined.
3 Cumulative results
3.1 Concentration statistics
TOC values ranged from 0.018 to 13.66 ppm C, with median
and mean concentrations of 0.546 and 0.902 ppm C, respec-
tively (Table 1). Samples in this study exhibited nearly the
lowest mean TOC value of all cloud water studies surveyed
in Fig. 1, with the other lowest values being over the Pacific
Ocean west of San Diego, California (0.85 ppm C), (Straub
et al., 2007) and East Peak, Puerto Rico (0.90 ppm C),
(Gioda et al., 2008, 2011; Reyes-Rodríguez et al., 2009).
The CAMP2Ex dataset exhibited the lowest minimum TOC
value of all shown studies. For context, the highest mean
and maximum TOC masses in cloud water studies were 34.5
and 51.7 ppmC, respectively, at Jeju Island, Korea, while the
peak dissolved organic carbon (DOC) mass in cloud water
was 85.6 ppm C at Mt. Tai, China. For comparisons to pub-
lished cloud water measurements, DOC and TOC are as-
sumed to be sufficiently similar in nature to directly com-
pare values. Differences in TOC between our study and other
work can partly be attributed to the different types of clouds
studied in the CAMP2Ex region (e.g., cumulus congestus,
cumulus, altocumulus, and altostratus) and the higher collec-
tion altitudes being conducive to enhanced liquid water con-
tents and droplet sizes compared with stratocumulus clouds
in regions like the northeastern (Straub et al., 2007) and
southeastern Pacific Ocean (Benedict et al., 2012). Previ-
ous studies have primarily sampled stratocumulus or stratus
clouds (Fig. 1). Also, some of our samples may have included
rain water, which naturally has lower TOC concentrations
than cloud water due to dilution (Fig. 1). To illustrate the im-
portance of this dilution effect, an average of the mean values
from the studies listed in Fig. 1 shows the following (ppm C):
fog =17.8, cloud =6.4, and rain =0.6. We further note that
direct comparisons of our results to others need to account
for the fact that water collectors have different transmission
efficiency behaviors as a function of droplet size, as well as
compositional differences across the droplet size spectrum
(i.e., Boris et al., 2016; Collett et al., 2008; Herckes et al.,
2013).
The order of species is as follows in terms of decreas-
ing average contribution of C mass relative to total TOC
(±1 standard deviation): acetate (14.7 ±20.5 %), formate
(5.4 ±9.3 %), oxalate (2.8 ±4.3 %), DMA (1.7 ±6.3 %),
succinate (1.6 ±2.4 %), pyruvate (1.3 ±4.5 %), glycolate
(1.3 ±3.7 %), adipate (1.0 ±3.6 %), MSA (0.1 ±0.1 %),
glutarate (0.1 ±0.2 %), and maleate (<0.1 ±0.1 %). An av-
erage of 70.0 % of TOC mass went unaccounted for. The pre-
dominant sources and production pathways of these species
are briefly explained here. Precursor emission sources for ac-
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C. Stahl et al.: Total organic carbon and the contribution from speciated organics in cloud water 14115
etate and formate include plants, soil, vehicles, and biomass
burning, with key production routes including the oxidation
of isoprene, the ozonolysis of olefins, and peroxy radical re-
actions (Khare et al., 1999, and references therein). Pyruvate
is considered the most abundant aqueous reaction product of
methylglyoxal, generated by the oxidation of gas-phase an-
thropogenic volatile organic compounds (Boris et al., 2014;
Carlton et al., 2006; Lim et al., 2013; Stefan et al., 1996;
Tan et al., 2010). Glycolate has been linked to aqueous pro-
cessing of acetate and is a precursor of glyoxylate (Boris et
al., 2014), which is formed via the oxidation of glycolalde-
hyde by hydroxide radicals (Thomas et al., 2016). Oxalate
is the most abundant dicarboxylic acid across different envi-
ronments (Cruz et al., 2019; Stahl et al., 2020; Yang et al.,
2014; Ziemba et al., 2011) and can be emitted directly by
biogenic sources (Kawamura and Kaplan, 1987), combus-
tion exhaust (Kawamura and Kaplan, 1987; Kawamura and
Yasui, 2005), and biomass burning (Narukawa et al., 1999;
Yang et al., 2014); however, it is also formed through the
oxidation and degradation of longer-chain organic acids and
acts as a notable tracer for cloud processing (Ervens et al.,
2004; Sorooshian et al., 2006). Saturated organics like glu-
tarate, adipate, and succinate are linked to fresh emissions,
mainly from the ozonolysis of cyclic alkenes (such as from
vehicular emissions), in the study region (Hatakeyama et al.,
1985; Stahl et al., 2020). Maleate can be secondarily formed
from the photooxidation of benzene (Rogge et al., 1993) or
from the primary emissions of combustion engines (Kawa-
mura and Kaplan, 1987). Alkyl amines (i.e., DMA) have
numerous sources such as biomass burning, vehicular emis-
sions, industrial activity, animal husbandry, waste treatment,
and the ocean (Youn et al., 2015). Finally, MSA is formed via
photooxidation reactions involving dimethylsulfide (DMS)
from oceanic emissions (Berresheim, 1987; Saltzman et al.,
1983) or dimethyl sulfoxide (DMSO) from anthropogenic
emissions (Yuan et al., 2004), in addition to being linked to
agricultural emissions and biomass burning (Sorooshian et
al., 2015).
Measured organic species were further grouped into cate-
gories: monocarboxylic acids (MCAs; glycolate, acetate, for-
mate, and pyruvate), dicarboxylic acids (DCAs; glutarate,
adipate, succinate, maleate, and oxalate), and measured or-
ganics (MO; the sum of MCAs, DCAs, MSA, and DMA).
Total MCA concentrations accounted on average for ∼75 %
of MO and were approximately 4 times larger than those
of DCAs. MO values ranged from 29.46 to 10 820 ppb, ac-
counting for an average of 30.0 % (median 23.8 %) of TOC
when masses were converted to just the C masses of the mea-
sured species (Table 1). Examples of other undetected organ-
ics include tricarboxylic acids, aromatics, alcohols, sugars,
carbohydrates, and aldehydes. Previous studies reported that
undetected species account for ∼45 % (Boris et al., 2016)
and 82.9 % (Boris et al., 2018) of organics. Interestingly,
the ionic charge balance for the 159 samples shows an an-
ion deficit (Fig. S1 in the Supplement), with a slope of 0.95
(i.e., anion charge on yaxis). This strong charge balance sug-
gests that detected organic species were balanced by cations
detected via IC analysis. Species contributing to the anion
deficit likely include a mix of unspeciated organic and inor-
ganic anions.
TOC was converted to total organic matter (TOM) by mul-
tiplying it by 1.8 (Zhang et al., 2005), as in other cloud wa-
ter studies (Boris et al., 2016, 2018), in order to compare it
to total measured mass (i.e., the sum of TOM, Na+, NH+
4,
K+, Mg2+, Ca2+, Cl−, NO−
2, Br−, NO−
3, and SO2−
4). We
caution that using a fixed 1.8 conversion value yields uncer-
tainty, as samples were collected in a range of air masses,
but 1.8 is a value that is fairly intermediate with respect to
those reported in the literature: 1.6 ±0.2 for urban aerosols
(Turpin and Lim, 2001), 2.07 ±0.05 in nonurban areas (Yao
et al., 2016), and values for biomass burning organic aerosols
ranging from 1.56 to 2.0 (Aiken et al., 2008; Turpin and
Lim, 2001) based on fuel type and combustion conditions
(Aiken et al., 2008). Higher values are expected for more
oxidized organics. Estimated TOM accounted for a median
and mean of 23.2 % and 30.7 % of total measured mass,
respectively, with the maximum for a single sample being
95.1 %. The median and mean ratios of MO to TOM were
38.1 % and 46.4 %, respectively. Furthermore, the median
and mean ratios of MO to total measured mass were 7.2 %
and 10.3 %, respectively, with a maximum of 57.6%. On av-
erage, chloride, sulfate, and nitrate were the most abundant
species (≥12.6 %), with the median and mean ratio of total
inorganic mass to TOM being 3.3 and 5.8, respectively. The
pH of the cloud water with TOC measurements ranged from
3.79 to 5.93 and averaged 5.04 ±0.51. The lowest pH values
all occurred over the ocean.
Our calculated percentages of MO relative to total mea-
sured mass are in contrast with results from a surface site
in Metro Manila (Stahl et al., 2020), where most of the
same organic species (adipate, succinate, maleate, oxalate,
and MSA) accounted for ∼1.3 % of the total aerosol mass,
excluding black carbon. Therefore, the first hypothesis of this
study – that the contributions of measured organic species ac-
count for a greater portion of total measured mass in cloud
water compared with surface particulate matter – holds true.
Gravimetry was used to measure total mass in the sur-
face measurements, whereas total measured mass was more
restrictive in cloud water in terms of being based on mea-
surable species, thereby qualifying our percentages as an
upper bound. However, the measured ions in cloud water
should contribute relatively more to total measured mass
in cloud water, owing to their hygroscopic nature (e.g., sea
salt) and the greater ease with which they become asso-
ciated with cloud water compared with more hydrophobic
species (Chang et al., 2017; Dalirian et al., 2018; Pringle et
al., 2010) like black carbon that contribute significantly to
total aerosol mass in the boundary layer of Metro Manila
(Cruz et al., 2019). For example, black carbon accounted
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14116 C. Stahl et al.: Total organic carbon and the contribution from speciated organics in cloud water
for 78.1 % and 51.8 % of the total mass between 0.10–0.18
and 0.18–0.32 µm in Metro Manila surface aerosol particles
(Cruz et al., 2019), respectively, which are size ranges that
are highly relevant to droplet activation. Air masses aloft in
the CAMP2Ex region, especially those processed by clouds,
are likely more aged and oxidized than fresh organic emis-
sions (e.g., automobiles, industry, and burning) in the sur-
face layer over Metro Manila, which is the most populated
urban area within the CAMP2Ex flight domain. Recent work
has shown that cloud processing of isoprene oxidation prod-
ucts (a key fraction of organic precursor vapors involved
with organic aerosol generation) is the main source of sec-
ondary organic aerosol (SOA) in the mid-troposphere (4–
6 km) (Lamkaddam et al., 2021). This motivates the exam-
ination of vertical TOC and organic species characteristics in
more detail, which is discussed next.
3.2 Vertical profiles
The vertical profiles of TOC mass were of interest, as they
relate to the general vertical distribution of organic matter
in the troposphere. Measurements off the coast of Japan ap-
proximately 2 decades ago during the ACE-Asia campaign
revealed unexpectedly high organic aerosol concentrations in
the free troposphere due to presumed SOA formation (Heald
et al., 2005). During that campaign, organic aerosol concen-
trations in the boundary layer and free troposphere, and their
relative contribution to total non-refractory aerosol mass (or-
ganic, SO2−
4, NO−
3, and NH+
4), were amongst the highest
of the various global regions examined (Heald et al., 2011).
Therefore, it is of interest to examine these types of vertical
profiles farther south in the CAMP2Ex region where data are
more scarce, with the unique aspect of this work being the
focus on cloud water composition.
The highest TOC masses were observed in the bottom
2 km, with a general reduction above that altitude (Fig. 3).
The decrease in the TOC concentration with respect to al-
titude could be attributed to more dilution in larger droplet
sizes; the results of cloud microphysical data will be the
focus of forthcoming work. Four data points influenced by
biomass burning were singled out (red markers Fig. 3a)
as they had systematically higher TOC masses than other
points. Those points will be discussed in more detail in
Sect. 4, and it is noteworthy that clouds were impacted by
biomass burning across a wide range of altitudes up to al-
most 7 km.
Focusing on the non-biomass burning (non-BB) data, there
was considerable variation in TOC in the bottom 2 km,
with concentrations as low as 0.144 ppm C and as high as
3.362 ppmC. Interestingly, cloud water collected above 5 km
still tended to show enhanced TOC masses, reaching up to
1.530 ppm C (6.1 km) among the non-BB points. The com-
position contributing to TOC was similar with altitude in
non-BB and biomass burning (BB) conditions, with ∼75 %
of TOC mass unaccounted for by the measured species and
MCAs dominating the measured organic mass (Fig. 3b).
The exception to that was the high-altitude BB point where
95.6 % of TOC was unassigned. Figure 3c–d show that there
was some qualitative agreement in the vertical profile of
AMS organic and m/z 44 mass concentrations for data col-
lected immediately adjacent to the cloud water samples in
cloud-free air; more specifically, the highest concentrations
of AMS organic mass, m/z 44 mass, and TOC were in the
bottom 2 km. However, some interesting differences exist, as
they related to specific air mass types, as will be discussed in
Sect. 4. Some differences could be rooted in how AMS data
represent submicrometer particles whereas cloud water data
encompass a wider range of particle sizes that activated into
cloud droplets (including supermicrometer dust and sea salt
particles) and also gases partitioning to cloud water.
Vertical profiles of ratios representative of the relative
amount of oxidized organics are shown in Fig. 4. The
MO : TOC ratio was quite variable with altitude, ranging
from 0.16 to 0.32 based on the locally averaged curve shown;
individual sample values ranged from 0.01 to 0.92. Vertically
resolved ratio values for f44 in cloud-free air and in cloud
(downstream CVI) ranged on average from 0 to 0.35 and
from 0.13 to 0.35, respectively. While mass concentrations
decreased with altitude (Fig. 3), ratios relevant to the degree
of organic aerosol oxidation and makeup of the organic com-
ponent of cloud water did not exhibit a clear change with
altitude.
4 Case studies
Four subsets of samples are examined here to probe how the
organic nature of cloud water varies for distinct air masses.
Sources of the air masses are visually shown in Fig. 5 based
on 5 d HYSPLIT back trajectories: (i) “North” (RF11, n=
20) collected off the northern coast of Luzon with influence
from East Asia, the Korean Peninsula, and Japan; (ii) “East”
(RF13, n=11) collected off the eastern coast of Luzon with
back trajectories traced to southern China with subsequent
passage across Luzon before arriving in the sample collec-
tion area; (iii) “Biomass Burning” (RF09, n=4) collected
to the southwest of Luzon above the Sulu Sea with influ-
ence from biomass burning plumes from Borneo and Suma-
tra primarily consisting of peat as the fuel type (Field and
Shen, 2008; Levine, 1999; Page et al., 2002; Stockwell et
al., 2016; Xian et al., 2013); and (iv) “Clark” (RF04, RF06,
RF07, RF09, RF10, and RF11, n=25) collected around the
operational area over Luzon, approximately ∼90 km north-
west of Metro Manila, with back trajectories extending to the
west and southwest of Luzon.
Biomass burning samples were identified based on the fol-
lowing criteria: flight scientist notes, elevated surface smoke
concentrations and aerosol optical depth (AOD) from the
NAAPS model, and the remarkable enhancement in chemi-
cal concentrations in cloud water. TOC, K+, SO2−
4, and NH+
4
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C. Stahl et al.: Total organic carbon and the contribution from speciated organics in cloud water 14117
Figure 3. (a) Vertical profile of TOC concentrations (n=159 samples) with the smaller inset including the four samples with enhanced
TOC owing to biomass burning (BB) influence. (b) Mass fractions of different subsets of species contributing to TOC at high (>5 km), mid
(2–5 km), and low (<2 km) altitude, with the beige area representing undetected species. Vertical profile of AMS (c) organic and (d) m/z 44
mass concentrations corresponding to spatially and temporally adjacent cloud-free periods of the collected cloud water samples. Colors in
panels (a),(b), and (d) represent the case study points in Sect. 4: North (green), East (purple), Biomass Burning (red), Clark (blue), and
non-case points (gray). The solid black lines in panels (a),(b), and (d) represent locally weighted average values. The error bars represent
1 standard deviation of the altitude variance.
Figure 4. Vertical profile of (a) the ratio of C mass from measured organics (MO) to TOC for cloud water samples, (b) AMS f44 in cloud-free
air and (c) AMS-CVI f44 in cloudy air. AMS data in panel (b) correspond to cloud-free periods that were spatially and temporally adjacent
to the collected cloud water samples, while the data in panel (c) are within the period of cloud water collection times in cloud. Colors in
panels (a),(b), and (d) represent the same case study points as in Fig. 3: North (green), East (purple), Biomass Burning (red), Clark (blue),
and non-case points (gray). The black lines in panels (a),(b), and (d) represent locally weighted average values.
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14118 C. Stahl et al.: Total organic carbon and the contribution from speciated organics in cloud water
Figure 5. Spatial summary of 120 h back trajectories for each sam-
ple included in respective case study sample sets: North (green; n
=20), East (purple; n=11), Biomass Burning (red; n=4), and
Clark (blue; n=25).
in particular were enhanced in these samples with concentra-
tions exceeding 4 ppm C, 0.13 ppm, 2.3 ppm, and 2.5 ppm,
respectively.
The vertical profile results shown previously (Figs. 3, 4)
display markers corresponding to these four case studies.
With the exception of one BB sample collected at 6.5km,
samples in the four cases were obtained below 3.3 km.
4.1 North
This category of samples was unique in that the mean MO
(527.5 ±301.6 ppb) and TOC (636.1±230.4 ppb C) concen-
trations were the lowest of all four cases (Table 2). The
largest three organic contributors to TOC (±1 standard de-
viation) were acetate (177.8 ±72.96 ppb C; 11.5 ±4.0 %),
oxalate (148.7 ±81.47 ppb C; 6.0 ±1.3 %), and formate
(83.16 ±79.65 ppb C; 3.0 ±2.2 %). Maleate and DMA were
not detected for this case, and 73.3 % of TOC went unac-
counted for. Samples in this category were collected between
1.2 and 2.9 km, without any pronounced organic chemical
trends with altitude (Figs. 3, 4).
This case exhibited a few distinct features worth not-
ing. First, it had the highest sea salt presence based on the
highest case-wide concentrations of Na+(3238 ±2861 ppb),
Cl−(5277 ±4333 ppb), Mg2+(347.1 ±328.3 ppb), and Br−
(15.56 ±8.036 ppb), the latter of which is a trace compo-
nent of sea salt (Seinfeld and Pandis, 2016). MSA originates
partly from marine emissions of DMS, but its concentra-
tion was among the lowest of all species for all four cases
with a mass contribution to total TOC (based on C mass)
of only 0.17 ±0.05 % in the North category (Table 3). In
their analysis of aerosol data in the surface layer of Metro
Manila, Stahl et al. (2020) showed lower overall organic
acid aerosol concentrations in the northeast monsoon sea-
son where northeasterly air masses originated predominantly
from East Asia; Stahl et al. (2020) also showed that those
air masses were characterized by an enhancement in organic
acid masses in the supermicrometer size range owing to ad-
sorption to coarse particle types such as sea salt and dust,
although with a preference for dust (Mochida et al., 2003;
Rinaldi et al., 2011; Sullivan and Prather, 2007; Turekian et
al., 2003). As there was no direct evidence of dust in this case
because the Ca2+:Na+ratio was on average (0.04) nearly
the same as sea salt (0.038) (Seinfeld and Pandis, 2016), or-
ganic acids could have interacted with sea salt. There were
strong correlations between sea salt constituents, TOC, and
almost all detected organics (Table S1 in the Supplement).
The second notable feature of this case was limited air
mass aging characteristics based on speciated ratios. The
acetate : formate ratio is often used to indicate the rela-
tive influence of fresh emissions (higher ratios) as com-
pared to secondary production (lower ratios) (Talbot et al.,
1988; Wang et al., 2007). In at least one study, fresh emis-
sions were linked to cloud water ratios above 1.5 and aged
samples having values below 1 (Coggon et al., 2014). The
mean acetate : formate ratio for this air mass category was
4.21 ±3.26, which was the highest of all four categories in
Table 2, suggestive of fresh emissions and low aging. This
was consistent with the Cl−:Na+ratio (1.70 ±0.13) being
close to sea water (1.81); our use of this ratio in the study
assumes that these species originate primarily from sea salt.
Lower Cl−:Na+values in the study region coincide with
sea salt reactions with acids such as sulfuric, nitric, and or-
ganic acids (AzadiAghdam et al., 2019). This was one of the
two cases that had adipate present, with this category exhibit-
ing the highest mean concentration (5.146 ±6.266 ppb). This
suggests that there was influence from cyclic organics possi-
bly originating from combustion sources, among others, dur-
ing transport to the sample region. Adipate exhibited negative
correlations with almost all other organic species in this case
(rfrom −0.48 to −0.72), suggestive of limited aging to form
shorter-chain carboxylic acids via photochemical reactions
(Table S1 in the Supplement). With the exception of adipate,
interrelationships between the other organics detected in this
case exhibited positive and significant correlations with one
another, which is suggestive of common precursors and/or
production mechanisms. Therefore, the results of the North
case point to influences from marine emissions and limited
aging signatures based on speciated ratios.
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C. Stahl et al.: Total organic carbon and the contribution from speciated organics in cloud water 14119
Table 2. Speciated concentrations of organics (ppb) for each case study: the first group of rows is monocarboxylic acids (MCAs); the second group of rows is dicarboxylic acids (DCAs);
the third group of rows is other organics, including total measured organics (MO) and total organic carbon (TOC); the fourth group of rows is inorganic ions; and the fifth group is select
ratios. nstands for number of samples, Ace denotes acetate, and For represents formate.
North (n=20) East (n=11) Biomass Burning (n=4) Clark (n=25)
Min Max Median Mean SD Min Max Median Mean SD Min Max Median Mean SD Min Max Median Mean SD
Glycolate 5.963 37.18 15.80 17.59 9.15 5.339 30.00 12.21 13.68 7.249 <DL 46.86 7.20 15.31 22.10 <DL 53.42 6.900 11.68 14.61
Acetate 1.935 288.8 184.9 177.8 72.96 301.7 423.5 358.6 359.0 40.71 47.85 3926 1704 1845 1668 <DL 1105 185.2 296.7 325.8
Formate 10.28 232.2 62.66 83.16 79.65 61.02 492.8 248.3 258.2 122.2 151.0 3819 2370 2178 1589 2.422 1041 152.0 266.1 316.8
Pyruvate 2.143 126.5 35.91 42.98 38.98 7.502 78.24 24.65 32.25 21.01 <DL 296.9 103.4 125.9 126.1 1.072 161.8 16.08 30.31 35.84
MCAs 25.32 632.2 299.9 321.5 183.6 431.3 923.7 673.2 663.2 142.7 245.7 8042 4184 4164 3336 31.93 2066 369.2 604.7 641.9
Glutarate <DL 10.18 <DL 1.527 2.758 <DL 10.86 4.074 5.122 3.672 62.46 258.7 140.2 150.4 82.20 <DL 62.46 1.358 9.423 16.85
Adipate <DL 17.44 <DL 5.146 6.266 <DL <DL <DL <DL <DL <DL <DL <DL <DL <DL <DL 37.43 <DL 3.777 7.888
Succinate <DL 136.2 28.09 42.30 47.84 15.45 176.9 63.90 74.11 57.27 24.58 1372 416 557.0 575.6 <DL 498.5 18.96 67.74 123.7
Maleate <DL <DL <DL <DL <DL <DL <DL <DL <DL <DL <DL 11.61 5.360 5.583 6.456 <DL 14.73 <DL 2.714 4.170
Oxalate 37.53 330.4 124.8 148.7 81.47 52.51 311.2 123.3 153.6 81.06 303.8 1135 520.1 619.7 360.1 5.547 448.9 43.63 88.33 103.9
DCAs 67.84 467.1 149.3 197.6 125.2 80.60 493.4 194.1 232.9 136.4 735.8 2766 914.6 1333 968.9 7.673 1010 72.10 172.0 238.0
MSA 1.550 14.72 7.748 8.290 3.160 3.10 17.82 10.07 10.57 4.400 <DL 24.79 3.874 8.135 11.69 <DL 10.85 3.874 4.184 3.620
DMA <DL <DL <DL <DL <DL <DL <DL <DL <DL <DL <DL <DL <DL <DL <DL <DL 61.25 <DL 6.454 15.89
MO 99.36 1089 483.8 527.5 301.6 567.0 1364 855.6 906.6 269.4 1017 10820 5094 5505 4187 54.05 3054 433 787.3 837.3
TOC 364.0 1085 555.0 636.1 230.4 663.0 1570 985.0 1051 330.6 4974 13660 7366 8342 3730 220.0 3362 849 1181 920.2
Na+693.2 11 870 2273 3238 2861 617.7 6546 1970 2569 1738 832.6 4425 2160 2394 1624 12.28 5870 624.9 1105 1403
NH+
4180.6 1955 644.4 847.0 515.5 512.7 2379 1307 1432 587.4 2517 8099 3685 4496 2483 45.29 2880 946.8 1009 814.6
K+13.83 404.9 49.69 88.89 99.63 18.32 493.0 66.14 122.9 136.0 132.2 724.3 272.3 350.3 258.4 2.462 264.0 31.82 63.07 75.51
Mg2+41.42 1338 236.3 347.1 328.3 62.35 668.1 209.4 273.2 182.7 83.62 500.5 242.3 267.2 191.2 <DL 631.2 64.73 117.2 152.6
Ca2+<DL 764.9 96.85 173.8 218.9 49.47 778.2 166.5 269.2 219.1 105.7 533.5 236.0 277.8 209.7 38.83 903.5 176.8 230.3 183.6
Cl−1445 18 520 3772 5277 4333 900.2 8357 2760 3510 2196 1126 5989 2553 3055 2124 45.43 9083 990.6 1716 2107
NO−
2<DL <DL <DL <DL <DL <DL <DL <DL <DL <DL <DL 5.598 1.339 2.069 2.670 <DL 16.06 <DL 3.427 5.126
Br−3.496 35.66 12.59 15.56 8.036 2.098 6.992 4.195 4.132 1.482 1.398 6.293 2.448 3.147 2.174 <DL 13.29 1.398 2.545 3.204
NO−
3477.2 5265 1197 1810 1506 1084 8724 2902 3772 2296 1880 7045 3344 3903 2277 64.84 2759 691.3 930.8 736.1
SO2−
41305 12 120 3281 4503 2865 1212 5296 2819 3223 1385 2313 9993 4177 5165 3343 23.39 4406 1157 1416 1157
pH 3.92 4.92 4.48 4.40 0.25 4.27 4.92 4.51 4.51 0.20 3.96 4.65 4.35 4.33 0.29 4.66 5.76 5.25 5.29 0.33
Ace /For 0.19 9.66 2.65 4.21 3.26 0.75 5.67 1.52 1.93 1.51 0.32 1.03 0.70 0.69 0.30 0 3.86 0.98 1.12 0.84
Cl−/Na+1.52 2.08 1.69 1.70 0.13 1.28 1.51 1.40 1.40 0.06 1.07 1.43 1.35 1.30 0.16 1.38 3.70 1.69 1.84 0.56
Ca2+/Na+0 0.08 0.04 0.04 0.02 0.05 0.14 0.10 0.10 0.03 0.08 0.13 0.12 0.11 0.02 0.05 6.17 0.32 0.99 1.46
K+/Na+0.02 0.03 0.02 0.02 0.01 0.03 0.08 0.04 0.04 0.01 0.10 0.18 0.16 0.15 0.04 0.01 3.93 0.05 0.25 0.78
MO /TOC 0.07 0.37 0.29 0.27 0.08 0.18 0.42 0.29 0.31 0.07 0.04 0.28 0.26 0.21 0.11 0.03 0.57 0.19 0.20 0.13
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14120 C. Stahl et al.: Total organic carbon and the contribution from speciated organics in cloud water
Table 3. Average organic composition for each case study where the first, second, and third groups of rows show the percentage contributions
(%) of individual components to monocarboxylic acids (MCAs), dicarboxylic acids (DCAs), and total organic carbon (TOC), respectively.
Group Species (%) North (n=20) East (n=11) BB (n=4) Clark (n=25)
Mean SD Mean SD Mean SD Mean SD
MCAs Glycolate 7.20 9.20 1.84 0.81 5.09 9.87 17.65 29.05
Acetate 64.03 17.74 64.20 10.85 45.86 14.07 46.35 23.98
Formate 16.54 9.83 28.62 10.35 46.40 7.24 29.09 11.72
Pyruvate 12.23 6.90 5.33 2.87 2.65 1.87 6.91 4.90
DCAs Glutarate 0.65 1.00 2.91 1.41 17.15 9.28 4.02 5.02
Adipate 8.04 9.47 0 0 0 0 16.05 21.48
Succinate 20.82 20.08 38.52 12.15 41.95 25.27 26.53 25.39
Maleate 0 0 0 0 0.75 0.88 3.20 5.93
Oxalate 70.49 12.29 58.57 11.52 40.16 16.50 50.20 17.42
TOC MSA 0.17 0.05 0.13 0.04 0.01 0.02 0.06 0.07
DMA 0 0 0 0 0 0 0.43 1.17
MCAs 17.79 6.17 23.66 5.99 16.03 10.13 16.28 11.91
DCAs 8.75 2.65 6.82 2.94 5.21 1.60 3.70 2.67
MO 26.72 7.86 30.61 7.35 21.25 11.32 20.46 13.34
Undetected 73.28 7.86 69.39 7.35 78.75 11.32 79.54 13.34
4.2 East
The dominant organic contributors to TOC
(1051 ±330.6 ppb C) in the East case were the same as
in the North case with the difference being the order after
acetate (±1 standard deviation): acetate (359.0 ±40.71 ppb;
14.9 ±3.1 %), formate (258.2 ±122.2 ppb; 7.2 ±3.8 %), and
oxalate (153.6 ±81.06 ppb; 3.8 ±1.2 %). The percentage
of TOC unaccounted for by the speciated measurements
(69.4 %) was the lowest out of all of the cases. This case
resembled the North case in that there was marine influence,
although the differences were a more pronounced dust
influence and greater evidence of aging based on chemical
ratios. Marine signatures come from the second highest
concentrations of Na+, Cl−, and Mg2+after North, with
high correlations between these species (Table S2).
Unlike the previous case, the Ca2+:Na+ratio (0.10)
was elevated from that of typical sea salt (0.038). Wang et
al. (2018) showed that East Asian dust can get lofted up dur-
ing dust storms, which could contribute to the transport to
the Philippines. Previous studies have shown that organic
acids adsorb more readily to dust compared with sea salt
due to dust’s more alkaline nature (Stahl et al., 2020; Sul-
livan and Prather, 2007). While Ca2+was correlated with 6
of the 11 organic species for this case (r=0.70–0.96; Ta-
ble S2), the magnitude of the correlations was very similar to
those between either Na+or Cl−and the speciated organics.
TOC also exhibited similar correlations with Na+, Cl−, and
Ca2+(r=0.83–0.87). Therefore, it is too difficult with the
given data to assert whether (if at all) the organic acids had
a preference towards either salt or dust aerosol particles; of
note, however, is that oxalate exhibited the strongest correla-
tion with either Na+, Cl−, or Ca2+(r=0.96–0.99) among
all species and also TOC. Additionally, Park et al. (2004)
showed enhanced Ca2+and NO−
3in the coarse mode owing
to continental Asian dust. In the East case, speciated organics
were fairly well correlated with NO−
3(r=0.68–0.99), which
has been associated with adsorption onto coarse aerosol types
like dust and sea salt (e.g., Maudlin et al., 2015; Stahl et al.,
2020). Nitrate was especially well correlated with Na+, Cl−,
and Ca2+(r=0.98–1.00), which exceeded correlations of
other common inorganic ions such as SO2−
4and NH+
4.
The vertical profiles clearly show the systematically higher
TOC masses relative to the North case across roughly the
same altitude range (1.3–3.3 km); however, the AMS organic
and m/z 44 values (although sparse) were more compara-
ble, which again can simply be due to the differences in what
is being measured, with AMS not accounting for the super-
micrometer particles types (i.e., dust and sea salt) that were
likely more influential in the cloud water in the East case.
However, the importance of droplet uptake of water-soluble
organic gases should also be considered, as they can influ-
ence TOC mass.
Evidence of greater aging compared with the North case
comes from a few ratios of interest. The Cl−:Na+ratio for
this case (1.40 ±0.06) was lower than for the North case,
suggestive of more sea salt reactivity aided by presumed
aging. Furthermore, the acetate : formate ratio (1.93 ±1.51)
was less than half the value from the North case. More
broadly, the overall contribution of MCAs and DCAs to TOC
were very similar between the North and East cases and also
the next two cases: MCA :TOC =16.03 %–23.66 %, and
DCA :TOC =3.70 %–8.75 % (Table 3). In contrast with the
North case, this category of samples had weaker interrela-
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C. Stahl et al.: Total organic carbon and the contribution from speciated organics in cloud water 14121
tionships between organic species, which was presumed to
be due to the mixture of sources impacting this case includ-
ing dust, marine particles, and likely other anthropogenic and
biogenic sources over land.
4.3 Biomass Burning
The Biomass Burning (BB) category samples exhibited the
highest concentrations of TOC (8342 ±3730 ppb C) and al-
most every organic, with the dominant contributors to TOC
(±1 standard deviation) being formate (2178 ±1589 ppb;
7.0 ±4.5 %), acetate (1845 ±1668 ppb; 8.4 ±5.6 %), and
succinate (557.0 ±575.6 ppb; 2.4 ±1.7 %). As acetate and
formate were so abundant, the relative enhancement of MCA
mass was much larger than DCA mass compared with the
three other cases examined (Table 2). While the correlation
matrix for this case was quite sparse in terms of significant
values, owing partly to the use of only a few points (n=4),
TOC and K+were highly correlated (r=0.99), which
demonstrates the strong linkage between TOC and biomass
burning emissions (Table S3) as also shown by others (Cook
et al., 2017). For context, Desyaterik et al. (2013) reported
cloud water TOC masses of 100.6 ppm C in a biomass burn-
ing air mass at Mt. Tai in eastern China that were 8 times
higher than typical values in the absence of agricultural burn-
ing. Cook et al. (2017) observed significantly higher cloud
water TOC masses during wildfire periods (16.6 ppm C)
at Whiteface Mountain, New York, than during biogenic
(2.16 ppm C) or urban (2.11 ppm C) periods.
In our BB samples, mean values of succinate
(557.0 ±575.6 ppb), glutarate (150.4 ±82.20 ppb), and
pyruvate (125.9 ±126.1 ppb) were significantly elevated
above the other cases. Stahl et al. (2020) recently showed
that succinate, oxalate, and MSA were especially enhanced
in aerosol samples collected in the study region during BB
periods in the 2018 southwest monsoon season. Study-
wide peak concentrations of succinate (1372 ppb), oxalate
(1135 ppb), and MSA (24.79 ppb) were found in this case,
reinforcing those findings (Stahl et al., 2020). Unlike the
previous two cases, maleate was detected in BB samples
(5.583 ±6.456 ppb). Although maleate is associated with
combustion sources (Kawamura and Kaplan, 1987; Rogge
et al., 1993), such as from extensive ship traffic around the
sampling area, other studies have shown enhancements of
maleate in BB air masses (i.e., Mardi et al., 2019; Tsai et
al., 2013). The percentage of mass contributing to TOC that
was unaccounted for was 78.7 %, with the highest sample
at 6.5 km having 95.6 % undetected, which was surprisingly
large based on the prevalence of organic acids in biomass
burning emissions (Reid et al., 1998). Therefore, the second
hypothesis posed in this study is partly true in that the BB
case exhibited much higher TOC values; however, these
samples did not exhibit a greater contribution from organic
acids to TOC, as the North and East cases actually had
a greater contribution from such species. This highlights
the need for more attention to be paid to organic chemical
speciation in clouds impacted by biomass burning emissions,
as such a large portion of the TOC mass went unaccounted
for in this study.
While absolute concentrations of most organics were
greatly enhanced in BB, the relative contributions of indi-
vidual organics within the MCA and DCA subsets of species
also varied. Most notably in the MCA category, formate was
greatly enhanced with a mass contribution to total MCA
mass of 46.40 % versus 16.54 %–29.09% for other cases. In
the DCA population of species, glutarate and succinate ac-
counted for higher mass fractions in the BB case (17.15 %
and 41.95 %, respectively) than in the other three cases
(0.65 %–4.02 % and 20.82 %–38.52 %, respectively).
The Cl−:Na+ratio was 1.30 ±0.06 and suggestive of
Cl−depletion, which has been observed in other regions ex-
periencing biomass burning and has been linked to high con-
centrations of inorganic and organic acids (Braun et al., 2017,
and references therein). This is supported by how the val-
ues of MO, SO2−
4, and NO3−were the highest in this case
(Table 2). The acetate : formate ratio was 0.69 ±0.30, but
it is unclear how effective this and other ratios are as ag-
ing indicators when biomass burning is present, especially
as fuel type varies between regions. Talbot et al. (1988) and
Wang et al. (2007) both report that the acetate : formate ra-
tio is substantially larger in biomass burning samples, which
is contradictory to the ratios that are reported for this case
(0.32 to 1.03). This could be due to the fuel type or aging of
the biomass burning plume; however, this is speculatory and
should be examined more extensively.
4.4 Clark
Samples in this category were collected during ascents after
takeoff and descents during approaches to the airfield, which
allowed for sample collection closer to the surface than the
other categories (altitude range of 0.2–2.9 km). Clark Inter-
national Airport is located within the Clark Freeport Zone,
which is part of both the Pampanga and Tarlac provinces and
consists of five cities and municipalities: Angeles city, Ma-
balacat city, Porac, Capas, and Bamban. This gives the Clark
area a population of approximately 996 000 with a popula-
tion density of ∼3100 km−2, which is low in comparison
to the most populated city in the Philippines, Quezon City
in Metro Manila, with 2.94 million people and a population
density of ∼17 000 km−2(PSA, 2016). In addition to Metro
Manila just to the southeast (∼90 km), Clark lies between
Mt. Pinatubo to the west and Mt. Arayat to the east, which
are active and potentially active volcanoes, respectively.
The average TOC for this case (1181±920.2 ppb C) was
most similar to the East case and exhibited the most vari-
ability relative to the mean TOC value of all four cases,
which we attribute to numerous sources impacting these sam-
ples, including local and regional emissions, time of day
variability, local spatial variability, and number of flights.
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14122 C. Stahl et al.: Total organic carbon and the contribution from speciated organics in cloud water
This case exhibited the highest percentage of TOC mass
that was unaccounted for by speciated organics (79.5 %),
with the three largest measured contributors (±1 stan-
dard deviation) consisting of acetate (296.7 ±325.8 ppb;
9.6 ±9.5 %), formate (266.1 ±316.8 ppb; 4.8 ±3.3 %), and
oxalate (88.33 ±103.9 ppb; 1.7 ±1.0 %). A few notable fea-
tures are mentioned that are specific to this case. This was the
only case that had DMA present (6.454 ±15.89 ppb), albeit
with a low mass contribution to total TOC (0.43±1.17 %).
This case exhibited the highest mass fractions of maleate
(3.20 ±5.93 %) and adipate (16.05 ±21.48 %) relative to
DCA mass, suggestive of greater anthropogenic emission
influence and processed aromatic compounds. DMA was
only correlated with maleate (r=0.67) among the organic
species, which is suggestive of a similar source (Table S4).
Stahl et al. (2020) showed increased aerosol concentrations
of freshly emitted organics (i.e., phthalate and maleate) ow-
ing to the vast sources of combustion engines to the south-
east of the Clark area. Clark is situated near a major highway
that could also contribute to the high combustion sources, al-
though commercial aircraft emissions could also play a sig-
nificant role.
Because succinate peaked in concentration for this case
(498.50 ppb) and back trajectories originated from Borneo
and Sumatra, there may have been some influence from
biomass burning (Fig. 5). The K+:Na+ratio was elevated
(0.25) above that of sea salt (0.036) (Seinfeld and Pandis,
2016) and was even higher than the Biomass Burning case
(0.15), suggestive of local and/or regional biomass burning
influence. This case exhibited the highest mean Ca2+:Na+
ratio (0.99) and was well above the sea salt value (0.038),
which we presume could be largely linked to resuspended
and/or transported dust. For Metro Manila, Cruz et al. (2019)
showed that resuspended dust, especially linked to vehicu-
lar traffic, is an important source of dust in the study region.
Stahl et al. (2020) showed that adipate is most influenced by
crustal sources in the study region and was unique among the
studied organics in this work in that it exhibited a prominent
peak in the supermicrometer range based on surface aerosol
measurements in Metro Manila. Consistent with that work,
Ca2+was only correlated with adipate in the Clark samples
(r=0.71) among the studied organics (Table S4), adding
support for how organic acids like adipate can partition to
dust with the novelty here being that the signature was ob-
served in cloud water.
5 Conclusions
This work analyzed 159 cloud water samples collected over
a 2-month period as part of the CAMP2Ex airborne cam-
paign around the Philippines. TOC and a total of 11 organic
compounds comprised of 4 MCAs (glycolate, acetate, for-
mate, and pyruvate), 5 DCAs (glutarate, adipate, succinate,
maleate, and oxalate), MSA, and DMA were measured. The
measured organics were then compared to TOC to determine
the percentage of organic species measured compared with
the total organic composition. Notable results are summa-
rized below including responses to the two hypotheses pro-
posed at the end of Sect. 1.
TOC masses ranged widely between 0.018 and
13.66 ppm C from 0.2 to 6.8 km, with a mean value of
0.902 ppm C. The contribution (in C mass) of the 11 mea-
sured species to total TOC was on average 30%. Using a
conversion factor of 1.8 for organic matter relative to organic
carbon, the mean amount of total organic matter (TOM)
accounted for by our measured 11 species was 46.4 %.
Furthermore, the mean contribution of TOM and speciated
organics to total mass (inorganics +organics) was 30.7 %
(maximum of 95.1 %) and 10.3 % (maximum of 57.6 %),
respectively. The mean ratio of inorganic to TOM was
5.8. The study’s first hypothesis that the measured organic
species account for a higher mass fraction relative to total
mass compared with surface layer aerosol measurements
over Luzon, excluding black carbon (∼1.3 %) (Stahl et al.,
2020) holds true. This is likely owing to more processed air
masses aloft and the reduced influence of black carbon that
is so abundant in areas like Metro Manila (Cruz et al., 2019;
Hilario et al., 2020a). The uptake of water-soluble gases can
also attribute to greater organic mass contributions.
In terms of the chemical profile of the speciated or-
ganics, the order in decreasing contribution of C mass
relative to TOC was as follows (±1 standard devia-
tion): acetate (14.7 ±20.5 %), formate (5.4 ±,9.3 %), oxalate
(2.8 ±4.3 %), DMA (1.7 ±6.3 %), succinate (1.6 ±2.4 %),
pyruvate (1.3 ±4.5 %), glycolate (1.3 ±3.7 %), adipate
(1.0 ±3.6 %), MSA (0.1 ±0.1 %), glutarate (0.1 ±0.2 %),
and maleate (<0.1 ±0.1 %). Approximately 70.0 % of TOC
went unaccounted for, highlighting the complexity and dif-
ficulty of organic speciation in the study region, with this
value being fairly similar to other regions (Benedict et al.,
2012; Boris et al., 2016, 2018; Herckes et al., 2002; Raja et
al., 2008). Monocarboxylic acids dominated the speciated or-
ganic mass (∼75 %) and were about 4 times more abundant
than dicarboxylic acids, which is suggestive of a higher abun-
dance of gaseous species and precursors. It should also be
noted that MCAs have a higher volatility than DCAs, which
could contribute to the higher organic mass. Additionally,
the MCAs measured in this study were predominately short-
chain organics that have naturally higher volatilities (Chebbi
and Carlier, 1996; Wang et al., 2007).
Vertical profiles of TOC revealed higher concentrations in
the bottom 2 km with a reduction above that. Samples im-
pacted by biomass burning emissions were substantially en-
hanced in TOC and most speciated organic masses, rang-
ing in altitude from as low as 1.3 km to as high as 6.5 km.
While vertical profiles of AMS organic and m/z 44 mass
concentrations qualitatively resembled that of TOC with re-
ductions above 2 km, the vertical behavior of chemical ra-
tios relevant to the composition of the cloud (ratio of C mass
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C. Stahl et al.: Total organic carbon and the contribution from speciated organics in cloud water 14123
from measured organics to TOC) and aerosol organics (f44)
did not reveal any clear trend. For both non-BB and BB
samples, monocarboxylic acids uniformly dominated C mass
with ∼75 % of TOC mass unaccounted for across the range
of altitudes studied.
The second hypothesis in this study proved to be partly
true, as clouds impacted by biomass burning exhibited
markedly higher TOC values (4.974–13.66 ppm C) and
masses of most of the other species detected compared with
the other three categories of samples in Sect. 4 (North, East,
and Clark). However, the part of the hypothesis about speci-
ated organic acids contributing more to BB samples did not
hold true, as total measured organics accounted on average
for 21.25 % of TOC, which was lower than two of the other
categories of samples (North, 26.72 %, and East, 30.61 %).
Interestingly, the highest BB sample (6.5km) had 95.6 % of
the C mass unaccounted for by speciated organics. This high-
lights the need for increased attention to be paid to organic
speciation in clouds impacted by biomass burning.
Four categories of samples with different air mass history
characteristics were compared, revealing a few notable fea-
tures: (i) while speciated concentrations and TOC masses
varied considerably between the four cases, the contributions
of MCAs and DCAs (based on C mass) to TOC were remark-
ably similar with little variation (MCA :TOC =16.03 %–
23.66 % and DCA :TOC =3.70 %–8.75 %); (ii) dust and sea
salt tracer species were strongly correlated with most of the
speciated organics for the North and East cases, suggestive
of interactions between such species and coarse aerosol sur-
faces, as supported by past work (Stahl et al., 2020; Sulli-
van and Prather, 2007); (iii) for samples with limited aging
(North case) based on selected chemical ratio values, adi-
pate was more abundant and was negatively correlated with
smaller carboxylic acids; (iv) BB samples exhibited the high-
est TOC concentrations (8342 ±3730 ppb C) as well as sig-
nificantly elevated levels of individual organics such as ac-
etate, formate, succinate, glutarate, pyruvate, oxalate, and
MSA; and (v) the Clark case had a higher variability in TOC
(1181 ±920.2 ppbC) than the North and East cases, presum-
ably owing to a greater mix of influential sources such as
fresh anthropogenic emissions (e.g., enhanced maleate) as
well as the transport of biomass burning plumes from Bor-
neo and Sumatra (e.g., enhanced succinate), dust, and spa-
tial and temporal variances across different flights. Related to
dust, Ca2+was only correlated with adipate in the Clark sam-
ples, which is consistent with a recent study in Metro Manila
(Stahl et al., 2020) showing that adipate uniquely exhibits
a prominent supermicrometer peak among organic acids, at-
tributed to interactions with dust.
Data availability. All data used can be
found on the NASA data repository at
https://doi.org/10.5067/Suborbital/CAMP2EX2018/DATA001 (last
access: 10 August 2021). Specifically, the two datasets used in this
paper can be found at https://doi.org/10.5067/Airborne/CAMP2Ex_
Cloud_AircraftInSitu_P3_Data_1 (NASA/LARC/SD/ASDC,
2020a) and https://doi.org/10.5067/Airborne/CAMP2Ex_Aerosol_
AircraftInSitu_P3_Data_1 (NASA/LARC/SD/ASDC, 2020b).
Supplement. The supplement related to this article is available on-
line at: https://doi.org/10.5194/acp-21-14109-2021-supplement.
Author contributions. EC, RAB, CS, ABM, and AS designed the
experiment. All coauthors carried out various aspects of the data
collection. EC, CS, and AS conducted analysis and interpretation
of the data. CS and AS prepared the manuscript with contributions
from the coauthors.
Competing interests. The contact author has declared that neither
they nor their coauthors have any competing interests.
Disclaimer. Publisher’s note: Copernicus Publications remains
neutral with regard to jurisdictional claims in published maps and
institutional affiliations.
Special issue statement. This article is part of the special issue
“Cloud, Aerosol and Monsoon Processes Philippines Experiment
(CAMP2Ex) (ACP/AMT inter-journal SI)”. It is not associated with
a conference.
Acknowledgements. The authors acknowledge support from NASA
(grant no. 80NSSC18K0148) in the framework of the NASA
CAMP2Ex project. Rachel A. Braun acknowledges support from
the ARCS Foundation, Melliza Templonuevo Cruz was sup-
ported by the Philippine Department of Science and Technology’s
ASTHRD program, and Alexander B. MacDonald acknowledges
support from the Mexican National Council for Science and Tech-
nology (CONACYT).
Financial support. This research has been supported by the
National Aeronautics and Space Administration (grant no.
80NSSC18K0148).
Review statement. This paper was edited by Manvendra K. Dubey
and reviewed by two anonymous referees.
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