Introduction
Severe haze episodes occur frequently in Beijing and throughout the North
China Plain (NCP), especially in winter, posing substantial threats to
public health (Ding et al., 2016; Fu and Chen, 2017; Gao et al., 2017).
High concentrations of fine particles and reduced visibility are associated
with stagnant meteorological conditions, i.e., shallow boundary layers, weak
winds, and high relative humidity (RH) (Wang et al., 2014a; Cai et al.,
2017; Tie et al., 2017). The rapid formation of particulate sulfate is
considered one of the key drivers of haze pollution for several reasons:
sulfate is an important component of fine particles; it facilitates the
partitioning of gaseous ammonia into the particle phase; and it enhances
aerosol water uptake, changing the optical and chemical properties of
aerosols (Guo et al., 2014; Huang et al., 2014). Sulfate is also known to
impact climate and acid deposition (Charlson et al., 1992; Xie et al.,
2015).
Relationship between sulfate / SO2 molar ratio and RH.
The circles indicate hourly observations during the 2014 winter in urban Beijing and are colored according to the observed PM1 (particles with
diameter less than 1 µM) concentrations. The solid and dashed
curves represent, respectively, the exponential fitting between the observed
and modeled sulfate / SO2 ratios and the observed RH, i.e.,
y=0.05+7×10-3e0.06x (R2=0.6) and
y=0.04+5×10-4e0.07x (R2=0.3). Sulfate concentrations are
obtained from HR-AMS PM1 measurements, and the corresponding model
results are from WRF-Chem simulations.
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Most of the sulfate is of secondary origin, formed by the oxidation of
anthropogenic SO2 (He et al., 2018). The
exponential relationship between RH and the molar ratios of sulfate relative
to SO2, as observed during the 2014 winter in Beijing (Fig. 1; see Sect. 2)
and in many previous studies (Sun et al., 2013; Zheng et al., 2015b; Wang
et al., 2016), imply that heterogeneous chemistry (processes involving
both gas and aerosol phases) plays an important role in the production of
sulfate. Indeed, air quality model simulations fail to capture the rapid
increase in sulfate from clean to hazy periods when considering only the
oxidation of SO2 in the gas phase and in cloud/fog water, suggesting
missing heterogeneous sources of sulfate (Wang et al., 2014b; Zheng et
al., 2015a; Li et al., 2017a) (Fig. 1). Adding an apparent RH-dependent
heterogeneous uptake for SO2 on aerosols greatly reduces the negative
bias in the modeled sulfate concentrations (see Sect. 2) (Wang et al.,
2014b; Zheng et al., 2015a).
Several heterogeneous reaction pathways have been proposed (He et al.,
2014; Cheng et al., 2016; Wang et al., 2016; Li et al., 2017a; Hung et al.,
2018; Qin et al., 2018; Yu et al., 2018), including the oxidation of SO2 in
aerosol water (by NO2, transition-metal-catalyzed O2, or
H2O2) and on aerosol surfaces (by NO2 and/or O2). Their
relative importance for sulfate production in winter haze, however, is
unknown due to uncertainties in relevant reaction rates and estimates for
aerosol water pH values (most reaction pathways are pH-dependent) (Guo et
al., 2017b; Liu et al., 2017a; Li et al., 2018b; Wang et al., 2018; Zhao et
al., 2018). For example, Wang et al. (2016, 2018) found in laboratory
experiments that the rate for the oxidation of SO2 by NO2 strongly
depended on the types of seed particles. In another example, Cheng et
al. (2016) suggested that reactions of SO2 with NO2 in aerosol
water could be the source of missing sulfate given the neutralized feature
of haze aerosols (with a pH value of about 6 estimated with the ISORROPIA-II
thermodynamic equilibrium model). Guo et al. (2017b) argued that
the ISORROPIA-II calculation in Cheng et al. (2016) overestimated
aerosol water pH and that transition-metal-catalyzed O2 instead of
NO2 was the key oxidant of SO2.
Therefore, solution to the missing-sulfate problem (discrepancy between
observations and model results) in northern China winter haze remains
challenging and controversial. The term sulfate in the atmospheric chemistry
literature commonly refers to inorganic sulfate species. In addition to
inorganic sulfate, organosulfur compounds (OSs) have also been demonstrated
to be present in atmospheric aerosols, including organosulfates
(ROSO3-), sulfones
(RSO2R′), and sulfonates
(RSO3-) such as methanesulfonate
(CH3SO3-,
the deprotonated anion of methanesulfonic acid, MSA) and
hydroxyalkylsulfonates (RCH(OH)SO3-) (Eatough and
Hansen, 1984; Dixon and Aasen, 1999; Surratt et al., 2008; Tolocka and
Turpin, 2012; Sorooshian et al., 2015). OS may have been misidentified as
inorganic sulfate in previous ambient measurements, thus leading to a
positive observational bias (as described later). The formation of OS is
typically not included in air quality model simulations and thus can partly
explain the missing-sulfate problem if concentrations of these species are
appreciable. However, OS concentrations in northern China winter haze
aerosols have rarely been reported, and their formation mechanisms are also
unknown.
In this study, we interpreted measurement data collected by a
high-resolution time-of-flight aerosol mass spectrometer (HR-AMS) and a
single-particle aerosol mass spectrometer (SPAMS) in Beijing winter. We
demonstrated the possible presence of OS in haze aerosols and discussed the
potential of different OS species. Hydroxymethanesulfonate (HMS,
CH2(OH)SO3-) was found to likely be the primary OS component. We found that heterogeneous production rate of
HMS through the reaction of formaldehyde (HCHO) and SO2 was fast enough to
account for the identified OS by HR-AMS. Furthermore, we hypothesized that
HMS might lead to additional sulfate production through a mechanism
involving aqueous hydroxyl radicals (OH). Finally, we discussed the
implications of this heterogeneous HMS chemical mechanism for the missing-sulfate problem and also future research needs.
Methods
Field measurements
Aerosol and gaseous pollutants were measured in urban Beijing during winter
2014 (mid-November to mid-December) (Fig. S1 in the Supplement). Chemical
composition of non-refractory PM1 was measured by a HR-AMS
(Aerodyne Research, Inc., USA). Individual particles (0.2–2 µm)
were detected by a SPAMS (Hexin Analytical Instrument Co., China). The gas
and aerosol collector ion chromatography (GAC-IC) system determined the
concentrations of semi-volatile gases (HNO3, NH3, and HCl),
and commercial analyzers were used to measure black carbon (AE33, Magee
Scientific, USA), gaseous HCHO (AL4021, Aero-Laser GmbH, Germany), and
SO2 and O3 (Thermo Fisher Scientific Inc., USA).
Meteorological data were also recorded. Details are provided below and in
Table S1 in the Supplement.
HR-AMS measurements
Particles were vaporized by impaction on a heated surface (600 ∘C), and the resulting vapors were ionized by an electron impact ionization
source (70 eV) (DeCarlo et al., 2006; Sun et al., 2016). The positive
fragment ions generated were detected then using time-of-flight mass
spectrometry. The HR-AMS switched every 5 min between the mass-sensitive V mode (mass resolution of ∼ 2000) and the high-resolution W mode (mass resolution of ∼ 4500). A default
collection efficiency of 0.5 was assumed (Middlebrook et
al., 2012); because the mass fraction of ammonium nitrate was below 40 %,
the aerosol particles were moderately acidic (Song et
al., 2018), and a silica gel dryer was used to reduce RH in the sampling
line. The ionization efficiency calibrations were performed using pure
ammonium nitrate particles following Jayne et al. (2000),
and the default relative ionization efficiencies (RIEs), except for ammonium
that was calibrated by ammonium nitrate, were applied to all the chemical
species for mass quantifications. It is noted that the calibrated RIE values
of sulfate later in 2017 and 2018 ranged from 1.22 to 1.39 (unpublished
data), implying a possible overestimation of sulfate mass concentrations by
2 %–14 %. Mass concentrations of chemical components (ammonium,
sulfate, nitrate, chloride, and organics) and inorganic and organic
sulfur-containing fragment ions
(HySOx+ and CxHyOzS+) were
quantified with the standard data analysis software packages (Sueper
et al., 2018). These sulfur-containing ions were well separated
from adjacent peaks in the observed mass spectra and thus quantified with
high confidence (examples in Fig. S2). The uncertainty quantification of
chemical species followed Bahreini et al. (2009)
(details in Sect. S1 in the Supplement).
SPAMS measurements
The SPAMS (Li et al., 2011) was based on the same principle
as the ATOFMS (aerosol time-of-flight mass spectrometer) designed by
Prather et al. (1994). Ambient aerosol particles were introduced
and focused into a narrow beam using an aerodynamic lens. Particles passed
through two continuous 532 nm Nd:YAG lasers with velocities determined on
the basis of observed traveling times. The individual particles were
ionized using a 266 nm Nd:YAG laser, and both positive and negative ions
were generated and detected by bipolar time-of-flight mass spectrometry. The
Computational Continuation Core software framework based on MATLAB (The
MathWorks, Inc., USA) was used to analyze these ions. The negative ion peak
at m/z -111 has been assigned to HMS
(CH2(OH)SO3-) with no significant
interference from other species in previous laboratory and field studies
(Lee et al., 2003; Whiteaker and Prather, 2003; Dall'Osto et al., 2009;
Zhang et al., 2012). HMS-containing particles were identified by the
presence of a peak at m/z -111 with the absolute and relative peak areas
greater than 50 % and 0.5 %, respectively. The negative ion peaks at
m/z -155, -187, -199, and -215 were also analyzed in order to detect
individual organosulfate species. This technique has been employed to
measure individual organosulfates in different regions around the world
(Hatch et al., 2011a; Wang et al., 2017).
HCHO measurements
The AL4021 analyzer is based on the Hantzsch reaction (HCHO reacts with
acetylacetone and ammonia in aqueous solution to form α-α′-dimethyl-β-β′-diacetyl-pyridine which is excited at 400 nm and fluoresces at 510 nm). The
Hantzsch reagents were prepared every 3 days and were kept cool in a
refrigerator. A Teflon filter was installed at the sampling inlet to remove
particles from the air. This analyzer was calibrated with 1 µM HCHO
standard solution every 2 to 3 days during the field measurements. The
measurement uncertainty is ∼ 20 %, and the detection limit is
∼ 0.15 ppb (Hak et al., 2005).
GAC-IC measurements
Three semi-volatile gases (NH3, HNO3, and HCl) were measured with
a time resolution of 30 min. The instrument was modified based on the Steam
Jet Aerosol Collector (Khlystov et al., 1995) in order to
better apply to the heavily polluted conditions in China
(Dong et al., 2012). Gases were absorbed in a wet
annular denuder and quantified by ion chromatography analyzers.
Intercomparison experiments with filter sampling and other online methods
showed that the relative uncertainties in GAC-IC were within ±20 %
for major species (Song et al., 2018).
Approaches to estimating OS and methanesulfonate with HR-AMS
OSs are primarily fragmented into separate organic ions
(CxHyOz+) and inorganic
sulfur-containing ions
(HySOx+) with minimal
organic sulfur-containing ions
(CxHyOzS+), due to the low thermal
stability of OS and thermal vaporization and electron ionization of HR-AMS
(Farmer et al., 2010; Huang et al., 2015; Hu et al., 2017a). The sulfate
concentrations obtained by the standard HR-AMS data analysis are contributed
not only by inorganic sulfate but also by OS. (NH4)2SO4 is
considered the dominant inorganic sulfate species in northern China winter
haze aerosols due to the relatively high NH3 levels and the resulting
moderate particle acidity (Song et al., 2018). The presence of OS and its
contribution to the HR-AMS sulfate (considered as the total sulfate) may be
detectable using ratios between different HySOx+,
due to different fragmentation patterns of (NH4)2SO4 and OS (Hu
et al., 2017a). For example, the major HySOx+
from (NH4)2SO4 includes S+, SO+, SO2+,
SO3+, HSO3+, and H2SO4+, while some of
these (SO3+, HSO3+, and H2SO4+) are not
generated by HMS (Ge et al., 2012; Gilardoni et al., 2016). We observed in
Beijing winter that the six ratios of SO+/HySOx+
and SO2+/HySOx+
(HySOx+ refers to SO3+,
HSO3+, and H2SO4+) were highly correlated with each
other (r>0.9, P<0.001) and that all of these ratios significantly
increased with RH and PM1 concentrations (Figs. 2a, b and S3). From
the clean and dry conditions (average
PM1 = 10 µg m-3 and RH = 20 %) to the
haze (polluted and humid) conditions (average
PM1 = 160 µg m-3 and RH = 70 %), these
ion ratios increased by approximately 25 %–41 %. During clean and
dry periods, the observed ratios agreed well with values from pure
(NH4)2SO4 calibrations (Ge et al., 2012; Gilardoni et al., 2016;
Hu et al., 2017a), supporting the dominance of (NH4)2SO4 over
other sulfur-containing compounds. The variations in SO+/HySOx+
and SO2+/HySOx+ were unlikely to be due to changes in the acidity of
haze aerosols (a pH of about 4 to about 5 in both clean and haze conditions)
(Song et al., 2018), and no clear relationship was found between these
fragment ratios and the fraction of ammonium nitrate in haze aerosols (Chen
et al., 2018). Examples are given in Fig. S4.
The enhancements of SO+/HySOx+ and SO2+/HySOx+
under haze conditions may suggest the presence of additional sulfur
compounds, which should either not generate SO3+,
HSO3+, and H2SO4+ ions or have higher ratios of
SO+/HySOx+ and SO2+/HySOx+
relative to (NH4)2SO4. Since several types of OS (e.g.,
organosulfates and HMS) satisfy this requirement, the observed HR-AMS mass
spectra of inorganic sulfur-containing ions cannot be used to quantify the
speciation of OS but may allow an estimate of sulfate-equivalent OS
concentration (COS, µg m-3):
COS=MSO42-SOobs+-Rcd,SO+/HySOx+⋅HySOx,obs+‾MSO++SO2,obs+-Rcd,SO2+/HySOx+⋅HySOx,obs+‾MSO2+,
where SOobs+, SO2,obs+, and
HySOx,obs+ (SO3,obs+,
HSO3,obs+, and H2SO4,obs+) are
concentrations of the observed inorganic sulfur-containing ions,
MSO+, MSO2+, and MSO42- are
molar masses, and Rcd,SO+/HySOx+ and
Rcd,SO2+/HySOx+ indicate the average
ratios of the two corresponding ions observed during the clean and dry
periods. Rcd,SO+/HySOx+⋅HySOx,obs+‾ is considered to be the concentration of
SO+ attributable to inorganic sulfate, and its difference to SOobs+ represents the contribution of OS. The same applies to
Rcd,SO2+/HySOx+⋅HySOx,obs+‾. This approach results in a conservative
estimate of COS because (1) it is assumed that OS do not generate
SO3+, HSO3+, and H2SO4+ ions and
(2) several minor ions (e.g., S+ and 33SO2+)
generated by OS fragmentation are not taken into account (Hu et al., 2017b).
The uncertainty quantification of COS is provided in Sect. S1.
Possible presence of OS in Beijing winter haze aerosols.
(a) PM1 concentrations (left, gray-shaded area) and RH
(right, blue line). (b) Contributions of OS to TS (left,
green-shaded area) and ratios of SO+ to H2SO4+ (right,
black line). The ratios between the other inorganic sulfur-containing ions
are given in Fig. S3. (c) Sulfate-equivalent OS concentrations
(left, black line) and AWC (right, red line). The gray-shaded area in
(c) indicates the 1σ uncertainty range of OS concentrations
(on average ∼ 40 % during haze periods).
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The organic sulfur-containing ions CH3SO2+ and
CH2SO2+ were used as the signature fragments of
methanesulfonate (Ge et al., 2012). In our field measurements, an excellent
linear correlation (r=0.98, P<0.001) was observed between these two
ions, and the average ratio of CH3SO2+ to
CH2SO2+ (2.9 ± 0.1) was consistent with the value of
2.9 ± 0.3 from the HR-AMS mass spectrum of pure MSA particles found in
previous studies (Ge et al., 2012; Huang et al., 2015, 2017), confirming the
presence of methanesulfonate in haze aerosols (Fig. S5). We estimated the
levels of methanesulfonate using the observed CH3SO2+ and its
fraction in the total signal intensity of MSA standards identified in Huang
et al. (2017).
WRF-Chem air quality model simulation
The Weather Research and Forecasting model coupled with Chemistry (WRF-Chem;
version 3.5.1) (Grell et al., 2005) was adopted to simulate concentrations of
particulate sulfate and gas-phase HCHO during the 2014 winter
(November–December). Two nested domains were configured to cover East Asia,
and model results from the inner domain focused on northern China with a
horizontal resolution of about 27 km were used for analysis. The
meteorological initial and boundary conditions were obtained from the NCEP
FNL (Final) Operational Global Analysis (NCEP, 2000), and temperature,
moisture, and wind fields were nudged to constrain the accuracy of the
simulated meteorology. The chemical initial and boundary conditions were
provided from MOZART-4 global model simulations of trace gases and aerosols
(Emmons et al., 2010). The Lin microphysics scheme (Lin et al., 1983), Rapid
Radiative Transfer Model (Mlawer et al., 1997), Goddard shortwave radiation
scheme (Kim and Wang, 2011), Noah Land Surface Model (Chen and Dudhia, 2001),
and YSU planetary boundary layer scheme (Hong et al., 2006) were used for the
calculations of cloud microphysics, longwave radiation, shortwave radiation,
land surface, and boundary layer processes, respectively. The Carbon Bond
Mechanism version Z (CBM-Z) (Zaveri and Peters, 1999) gas-phase chemical
mechanism coupled with the thermodynamic module MOSAIC (Model for Simulating
Aerosol Interactions and Chemistry) (Zaveri et al., 2008) was applied to
simulate gas-phase reactions and aerosol processes.
Anthropogenic emissions were obtained from the MIX inventory (Li et al.,
2017b) for five sectors, namely power generation, industry, residential,
transportation, and agriculture, including the emissions of SO2,
NOx, CO, non-methane volatile organic compounds (NMVOCs),
NH3, and primary inorganic and organic particulate matters. In
addition, biogenic emissions were estimated using the Model of Emissions of
Gases and Aerosols from Nature (MEGAN) (Guenther et al., 2006), and open
biomass burning emissions were taken from the Global Fire Emissions Database
version 4 (GFEDv4) (Randerson et al., 2017). In the WRF-Chem model, sulfate
was formed by the oxidation of SO2 both in the gas phase (initiated by
OH) and in cloud/fog water (by dissolved H2O2, O3, and
transition-metal-catalyzed O2) (Pandis and Seinfeld, 1989):
SO2+OH+O2→SO3+HO2,HSO3-+H2O2→SO42-+H++H2O,SO2(aq)+O3→SO42-+O2,SO2(aq)+12O2⟶Mn2+,Fe3+SO42-,
where SO2(aq) represents the sum of SO2⋅H2O,
HSO3-, and SO32-.
We conducted two model
simulations: (1) a BASE scenario with normal settings and (2) a
5 × EMIS scenario in which primary HCHO emissions from the
transportation sector were elevated by a factor of 5. This is because, as
described in Sect. 3, the BASE scenario
significantly underestimated ambient HCHO concentrations. It remains unclear
whether primary or secondary sources of HCHO are responsible for its high
wintertime levels. Jobson and colleagues have recently suggested that HCHO
emissions during motor vehicle cold starts, especially in cold winter, are
significantly underestimated in current inventories (Jobson et al., 2017).
Accordingly, a 5 × EMIS scenario with increasing primary HCHO
emissions from transportation was conducted, which greatly reduces the
negative biases in the modeled HCHO and thus was used to calculate the
formation rate of HMS.
Apparent heterogeneous sulfate production rate
An apparent heterogeneous uptake of SO2 on aerosols has been shown to
be able to compensate for the missing sulfate (ΔSO42-) in
current air quality models during northern China winter haze episodes (Wang
et al., 2014b; Zheng et al., 2015a; Li et al., 2018b). The heterogeneous
sulfate production rate, PΔ, was parameterized with an uptake
coefficient γ (the fraction of gas–aerosol collisions resulting in
chemical reaction) (Jacob, 2000):
PΔ=Rp/Dg+4/vγ-1SpSO2(g)MSO42-,
where Rp is the average aerosol droplet radius taken as
0.15 µm following Cheng et al. (2016), Dg is the
gas-phase diffusion coefficient of SO2, v is the average molecular
speed of SO2, Sp is the aerosol surface area per unit
volume of air, and SO2(g) is the gas-phase
concentration. γ is 2 × 10-5 when RH ≤ 50 %
and increases linearly from 2 × 10-5 to 5 × 10-5
when 50 % < RH ≤ 100 % (Zheng et al., 2015a), consistent
with other laboratory and model studies (Wang et al., 2016; Li et al.,
2017a). The heterogeneous reaction rate required to produce the identified OS
(POS) can be expressed as
POS=COS/ΔSO42-⋅PΔ.
ISORROPIA-II thermodynamic equilibrium model calculation
We estimated aerosol water content (AWC), aerosol water pH, and ionic strength with the ISORROPIA-II
inorganic model (Fountoukis and Nenes, 2007) and also considered the
contribution of carbonaceous species. Detailed calculations were given in our
recent study (Song et al., 2018). Briefly, ISORROPIA-II predicts the phase
partitioning of an
NH4+-K+-Ca2+-Na+-Mg2+-SO42--NO3--Cl--H2O
aerosol and semi-volatile gases (HNO3, NH3, and HCl), and
can be used in either forward mode (the total (gas + aerosol) concentration
of each species is fixed) or reverse mode (the aerosol concentration of each
species is fixed). The forward-mode results were adopted in this study, since
the reverse-mode calculations of pH are sensitive to aerosol composition
measurement errors and should be avoided. The model inputs were taken from
the HR-AMS (bulk PM1 composition) and GAC-IC (semi-volatile gas)
measurements except for crustal species that were estimated based on their
levels in PM2.5 and typical size distributions (Song et al., 2018). The
inorganic aerosol phase state was assumed to be metastable, meaning that the
aqueous solution does not crystallize but remains supersaturated when the RH
is below the deliquescence RH, although aerosols may reside in a stable
state, meaning that the aqueous solution crystallizes once saturation is
exceeded (Rood et al., 1989). The assumed phase state led to a small
difference in pH (<0.01 units on average) and an average
∼ 20 % difference in AWC (Song et al., 2018) and thus did not
affect the major conclusions of this study. The AWC modeled by ISORROPIA-II
has been shown to be in good agreement with those based on ambient
measurements in northern China (Wu et al., 2018). The validity of pH
calculations was supported by the reasonable agreement between the predicted
and observed gas-particle partitioning of semi-volatile species (Song et al.,
2018).
The aerosol water associated with carbonaceous species was estimated with
the hygroscopicity parameter κ (Cheng et al., 2016).
κ values of 0.06 and 0.04 were used for organics and black carbon,
respectively (Song et al., 2018). The contribution of
carbonaceous species to AWC was found to be small (∼ 10 %),
leading to a minor effect on pH (∼ 0.05 unit). The ionic
strength of aerosol water was estimated using the predicted aerosol
composition and AWC (Herrmann, 2003). The uncertainty in pH was
estimated with a Monte Carlo approach accounting for measurement errors in
the model inputs including gas and aerosol species and meteorological
parameters. The 95 % confidence interval for calculated pH values was 4.1
to 5.5, very similar to the pH range found in previous northern China winter
haze studies (Song et al., 2018).
Kinetics and thermodynamics of HMS heterogeneous production
The chemical mechanism for HMS production can be expressed as
(Boyce and Hoffmann, 1984)
SO2⋅H2O↔HSO3-+H+,HSO3-↔SO32-+H+,
HCHO+HSO3-⟷k1CH2(OH)SO3-,HCHO+SO32-⟷k2CH2(O-)SO3-,CH2(OH)SO3-↔CH2(O-)SO3-+H+,CH2(OH)SO3H↔CH2(OH)SO3-+H+.
CH2(OH)SO3H (hydroxymethanesulfonic acid, HMSA) dissociates
twice to form CH2(OH)SO3- and CH2(O-)SO3- with
the dissociation constants pKa1<0 and pKa2∼12,
respectively, and thus, in the pH range of this study, the adduct existed as
CH2(OH)SO3-. The acid catalysis of HMS production was
significant only at pH < 1 and thus irrelevant in the present context
(Olson and Hoffmann, 1989). It is noted that CH2(OH)SO3- may
form salts by the neutralization reaction with ammonium or other cations
(e.g., Na+, K+, and Ca2+) and undergo precipitation when the
ambient RH becomes lower than the efflorescence RH value.
The production of HMS in aerosol water was not found to be limited by the mass transfer
processes and hydration of HCHO (Sect. S2). The rate for the heterogeneous
production of HMS, PHMS (in sulfate-equivalent
µg m-3 h-1), was calculated as
PHMS=k1α1+k2α2⋅SO2(aq)⋅HCHO(aq)⋅AWC⋅MSO42-,
where k1 and k2 were, respectively, the forward rate constants for
Eqs. (10) and (11), SO2(aq) (defined as the sum
of SO2⋅H2O, HSO3-, and SO32-) and
HCHO(aq) was aqueous-phase concentrations estimated
with their gas-phase levels and Henry's law constants. α1 and
α2 represented the fractions of HSO3- and
SO32- in SO2(aq), respectively, and both were
functions of pH. The production of HMS was reversible and the equilibrium
constant Keq could be expressed as
Keq=HMS(aq)/HMS(aq)SO2(aq),
where HMS(aq) was the
aqueous-phase concentration of HMS. Because the time to reach the
equilibrium under winter haze conditions was typically greater than that for
haze formation, the precursors and HMS were usually not equilibrated
(Sect. S3). The relevant physical and chemical properties of SO2, HCHO, and
HMS are summarized in Tables S2 and S3.
Results and discussion
The presence of OS in Beijing winter haze aerosols
The standard HR-AMS data analysis usually does not distinguish OS from
inorganic sulfate, since OSs are fragmented primarily into separate organic
ions and inorganic sulfur-containing ions (Hu et al., 2017a). Using the
distinct fragmentation patterns of inorganic sulfur-containing ions in the
observed HR-AMS mass spectra, we derived a conservative estimate of total OS
concentrations (expressed in sulfate-equivalent µg m-3) in
PM1 (particles with an aerodynamic diameter below 1 µM),
as described in Sect. 2. During several winter haze periods (defined as
PM1 > 100 µg m-3), OSs were estimated to
contribute significantly to the total sulfate (TS) identified by the standard
HR-AMS data analysis, with an average OS/TS ratio of 17 % ± 7 %
and a maximum ratio of 31 % (Fig. 2a–b). Thus, previously reported
sulfate concentrations in Beijing winter haze aerosols from HR-AMS
measurements may have been biased high due to the presence of OS.
A good positive correlation (r=0.82, P<0.001) was found between
OS and the AWC (Fig. 2c) estimated on the basis of the ISORROPIA-II
thermodynamic equilibrium model constrained using in situ gas and aerosol
compositional and meteorological measurements (see Sect. 2), suggesting that
aerosol water serves as a medium enabling the production of OS. It has been
shown that PM1 is in the liquid phase state during Beijing winter haze
periods (Liu et al., 2017b). In contrast, OSs were
unrelated to the presence or absence of cloud/fog events (Fig. S6),
indicating that the identified OSs were less likely formed by local cloud/fog
processing (Moch et al., 2018). Although our
interpretation of the HR-AMS fragmentation of inorganic sulfur-containing
ions cannot directly determine the speciation of OS (organosulfates,
sulfones, methanesulfonate, and hydroxyalkylsulfonates), we suggest, through
the following analyses, that HMS may be the major OS species in Beijing
winter haze aerosols.
Methanesulfonate, sulfones, and organosulfates are likely minor OS
species
The contribution of methanesulfonate to OS was only 2 %–8 % estimated
using CH3SO2+ as the characteristic fragment in the HR-AMS
mass spectra (see Sect. 2 and Fig. S5) (Huang et al., 2017). Its estimated
concentrations were comparable to those from a previous study (Yuan et al.,
2004). The methanesulfonate in Beijing winter is likely formed by the oxidation of dimethyl sulfite or dimethyl sulfoxide emitted from waste disposal (Yuan
et al., 2004). Aerosol water has been suggested to play important roles in
the formation of methanesulfonate and its condensation onto particles (Barnes
et al., 2006; Gaston et al., 2010).
The formation of bis-hydroxymethyl sulfone (C2H6SO4), the only sulfone
that has been identified in ambient aerosols, is inhibited by atmospheric
water and is thus unlikely to be important in winter haze (Eatough and
Hansen, 1984). Organosulfates, formed through reactions of gaseous organics
(e.g., epoxides and aldehydes) and particulate inorganic sulfate, also seem
to represent minor contributions to OS based on the following evidence. The
most common organosulfates identified previously in ambient aerosols, such as
glycolic acid sulfate (C2H3SO6-), 2-methylglyceric acid sulfate
(C4H7SO7-), isoprene epoxydiols sulfate
(C5H11SO7-), and benzyl (or methyl phenyl) sulfate
(C7H7SO4-) (Froyd et al., 2010; Hatch et al., 2011a; Ma et al.,
2014), were not detected by SPAMS measurements taken in Beijing winter.
The production of organosulfates is enhanced by increased aerosol acidity
(Surratt et al., 2010; Hatch et al., 2011b; Riva et al., 2016), whereas the
relatively high pH values of about 4 to about 5 for winter haze aerosols in
northern China may represent a limiting factor (Song et al., 2018).
Production and existence of HMS in Beijing winter haze aerosols.
(a) Schematic of heterogeneous HMS chemistry in northern China
winter haze. (b) NHMS (left, red line) and OS
concentrations (right, black line). NHMS was only available for a
haze episode in December 2014 due to instrumentation constraints.
(c) Gas-phase concentrations of observed SO2 (left, black
line) and modeled HCHO (right, blue line). (d) PHMS
(left, pink-shaded area) and POS (right, black line). The
pink-shaded area shows the uncertainty in PHMS due to the
estimated range of pH (4.1–5.5). The inserted figure indicates the linear
correlation of PHMS and POS at a pH of 5.5.
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HMS is likely the major OS species
Since the only known source of HMS (CH2(OH)SO3-) is the
nucleophilic addition of HSO3- and SO32- to HCHO in aqueous
solutions (Boyce and Hoffmann, 1984) (Fig. 3a; see Sect. 2), the
dominance of HMS in OS can explain the excellent correlation found between OS
and AWC (Fig. 2c). The other hydroxyalkylsulfonate species are estimated to
be less important than HMS, according to the laboratory experimental data
from Hoffmann and colleagues (Olson and Hoffmann, 1989) and the
abundance of different aldehydes in the atmosphere (Sect. S3).
Mass concentrations of HMS have been observed to be low, on the order of
0.01 µg m-3, during several field campaigns in the United
States, Germany, and Japan (Dixon and Aasen, 1999; Suzuki et al., 2001;
Scheinhardt et al., 2014). However, the heterogeneous production of HMS can be
fast during winter haze periods in northern China because of a moderately
acidic pH of aerosol water, high AWC, high precursor (SO2 and HCHO)
concentrations, and low temperature. First, laboratory experiments have
indicated that HMS production rates increase rapidly with pH, responding
mainly to the dependence of SO32- (a more efficient nucleophile than
HSO3-) on pH (Boyce and Hoffmann, 1984; Kok et al., 1986). Values of
aerosol water pH of about 4 to 5 obtained during the NCP winter haze events
(Song et al., 2018) are 2 to 3 units higher than typically found in North
America and Europe (Guo et al., 2017a), implying a factor of >104 enhancement in HMS production rates. Second, the AWC during winter
haze periods (on the order of 100 µg m-3) is among the highest
in the world (Nguyen et al., 2016), providing a reactor to facilitate aqueous reactions. Third, concentrations of both precursor gases are
relatively high. Gaseous HCHO has been measured to be about 6 ppb on average
in Beijing winter and increases on haze days (Rao et al., 2016). Although
emissions of SO2 have rapidly declined, especially since the implementation of the National Air Pollution Prevention and Control Action
Plan in 2013, its concentrations in the NCP remain much higher than in many
other parts of the world (Shao et al., 2018). Last, low temperature in winter
increases the solubility of precursor gases in water (Sander, 2015) and thus
enhances HMS production rates. The reaction rate constants for HMS production
decrease at low temperature but to a lesser extent (Boyce and Hoffmann, 1984).
Comparison of modeled and observed HCHO concentrations.
(a) BASE scenario. (b) 5 × EMIS scenario. The dots
are colored according to PM1 concentrations. Model results from
WRF-Chem are shown.
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In order to evaluate whether HMS production was fast enough to account for
the identified OS, we calculated the rate for HMS production in aerosol water
(PHMS) and compared this with the apparent heterogeneous reaction
rate that would be required to produce the identified OS (POS). As
described in Sect. 2, PHMS calculations involved concentrations
of gaseous SO2 and HCHO (Fig. 3c), Henry's law constants, AWC and pH
(95 % confidence interval: 4.1–5.5), and reaction rate constants from
laboratory experiments. HCHO concentrations simulated by the WRF-Chem air
quality model (5 × EMIS scenario; see Sect. 2) were used because its
measurements were available only in December. The modeled HCHO was well
correlated with its measured values (r=0.8, P<0.001) but was biased
low by ∼ 20 % (Fig. 4). PHMS was most sensitive to
particle acidity and increased rapidly with pH, becoming comparable to
POS when using the upper limit of pH (5.5) (Fig. 3d).
PHMS calculated here was expected to be conservative. Henry's law
constants and kinetic data were obtained in relatively dilute solutions,
while aerosol water constitutes a concentrated electrolyte solution. The high
ionic strength of aerosol water (∼ 11 M during haze periods) may
strongly increase formaldehyde solubility (Toda et al., 2014) and may further
enhance kinetic rates for HMS production (Sect. S4). Gaseous HCHO
concentrations used in the calculations were also biased low. It is very
likely that the actual PHMS was comparable to POS at a
pH below 5.5, within the uncertainty range of the calculated aerosol water
pH. Note that the production of HMS was a minor sink of HCHO because the
corresponding lifetime of ∼ 4 days was greater than that
of photolysis and oxidation by OH (∼ 1 day in Beijing winter).
Our field measurements with SPAMS confirmed the existence of HMS in winter
haze aerosols (Fig. 3b). Individual particles containing HMS were identified
by the characteristic mass-to-charge ratio m/z -111 (CH2(OH)SO3-)
in the SPAMS mass spectra (Whiteaker and Prather, 2003). The
observed number concentration of HMS-containing particles (NHMS) was
closely correlated with AWC (r=0.86, P<0.001), supporting the
production of HMS in aerosol droplets. A good relationship was also found
between NHMS and the identified OS from HR-AMS (Fig. 3b). Although the
SPAMS data showed a significant percentage (∼ 10 % during haze
periods) of HMS-containing particles in the total particle counts, a
quantitative estimate of HMS mass concentration is not available here because
HMS may be fragmented into smaller ions, such as HSO3- and SO3-,
depending on the countercations in particles (i.e., matrix effects) (Neubauer
et al., 1997; Whiteaker and Prather, 2003). These ions coexist with the HMS
peak in the SPAMS mass spectra (Fig. S7).
Implications of heterogeneous HMS chemistry
We have shown above in Beijing winter haze aerosols that a significant
fraction of the missing sulfate based on HR-AMS measurements may be
attributed to OSs, which likely exist primarily as HMS and are misidentified
as inorganic sulfate by the standard HR-AMS data analysis. If HMS is assumed
to represent the only OS compound, we estimated that it may account for about
one-third of the missing sulfate in Beijing winter haze aerosols (Fig. S8).
Interestingly, HMS would also likely be misidentified as inorganic sulfate
(SO42-) with typical ion chromatography (IC) analysis, another
common method used to determine aerosol chemical compositions. In fact,
nearly all of the particulate sulfate measurements in northern China winter
haze have been made using these two techniques (He et al., 2014, 2018; Cheng
et al., 2016; Wang et al., 2016; Li et al., 2017a). For anion detection in
IC, the pH of the carrier fluid (known as eluent, a solution of KOH, NaOH,
NaHCO3, etc.) is usually greater than 9 (Wang et al., 2005; Cao et
al., 2012; Liu et al., 2016; Han et al., 2017). HMS is unstable under such an
alkaline environment and dissociates rapidly into SO32- and HCHO
(Seinfeld and Pandis, 2016):
CH2(OH)SO3-+OH-→HCHO+SO32-+H2O.
The characteristic time for HMS dissociation at pH > 9 is less
than 1 min (Seinfeld and Pandis, 2016), much less than the retention
time of SO42-. The product SO32- can be rapidly oxidized to
SO42- by oxidants (e.g., O3 and H2O2) either
generated or dissolved in aqueous extracts.
As described in Sect. 2.6, HMS should exist as the CH2(OH)SO3-
anion in wet aerosols and may form salts with ammonium or other cations when
aerosol particles dry out. A possible fate of HMS is to be oxidized by
aqueous OH radicals producing peroxysulfate radicals
(SO5⚫-)
(HMS is resistant to H2O2 and O3) (Olson and
Fessenden, 1992):
CH2(OH)SO3-+OH+O2→HCHO+SO5⚫-+H2O.
SO5⚫- is an intermediate in the free-radical chain
reactions oxidizing SO2 to SO42-, and for each attack of
OH on HMS, multiple SO42- ions are produced (Fig. S9).
Importantly, an HCHO molecule is released by Eq. (17), suggesting that this
reaction pathway does not result in net consumption of HCHO and that HMS
serves as a temporary reservoir of tetravalent sulfur. We speculate from the
diurnal patterns of HMS production rates (PHMS) and the
identified OS concentrations that the oxidation of HMS by OH is likely to
occur during daytime (Tan et al., 2018) (Fig. S9). But the rate of Eq. (17)
should be relatively slow when compared with that of Eqs. (10)–(11) because
a significant level of HMS is expected to reside in the haze aerosol
particles. A quantitative rate estimation for this pathway, however, is
difficult because aqueous OH is short-lived and it can be derived as a result
of uptake from the gas phase or be generated or scavenged in the condensed
phase (Jacob, 1986; Ervens et al., 2014).
Future research needs
This study points to a potentially important role of heterogeneous HMS
chemistry in explaining the missing-sulfate problem during Beijing winter
haze episodes. HMS has also been suggested to promote new particle formation
by stabilizing sulfuric acid clusters (Li et al., 2018a). Although our field
measurements and data interpretation focus on Beijing, this chemical
mechanism should be important throughout the NCP because winter haze
pollution is regional, as indicated by the distribution of SO2 and
HCHO (Fig. S10). Different from many other proposed pathways for sulfate
production, HMS chemistry has a characteristic reaction product. More
accurate quantification of HMS (e.g., using capillary electrophoresis and ion
pairing chromatography; Munger et al., 1986; Scheinhardt et al., 2014) in
future field studies is essential to improve our understanding of this
mechanism. In addition, three-dimensional chemical transport model studies
should be conducted to further explore the HMS formation pathways and the
associated uncertainties (e.g., pH values). The modeling simulations may also
demonstrate whether significant amounts of HMS can be formed in cloud
droplets before being transported to the ground level (Eck et al., 2012; Li
et al., 2014). This study reveals the unappreciated role of HCHO in Chinese
haze through forming the complex HMS with SO2, and it should be noted
that HCHO also serves as a critical source of HOx
(OH + HO2) radicals by photolysis (Rao et al., 2016) and as a
carcinogen (Zhu et al., 2017). In spite of its importance, our knowledge of
the sources and chemical processes of HCHO during northern China winter haze
events remains limited. Further research should be conducted to elucidate
HCHO sources in the northern China winter and to design targeted mitigation
measures.