Iron-containing mineral aerosols play a key role in the oxidation
of sulfur species in the atmosphere. Simulated cloud processing (CP) of
typical mineral particles, such as illite (IMt-2), nontronite (NAu-2),
smectite (SWy-2) and Arizona Test Dust (ATD) is shown here to modify sulfur
dioxide (SO2) uptake onto mineral surfaces. Heterogeneous oxidation of
SO2 on particle surfaces was firstly investigated using an in situ DRIFTS
apparatus (diffuse reflectance infrared Fourier transform spectroscopy). Our results showed that the Brunauer–Emmett–Teller (BET) surface area normalized uptake
coefficients (γBET) of SO2 on the IMt-2, NAu-2, SWy-2 and
ATD samples after CP were 2.2, 4.1, 1.5 and 1.4 times higher than the
corresponding ones before CP, respectively. The DRIFTS results suggested
that CP increased the amounts of reactive sites (e.g., surface OH groups) on
the particle surfaces and thus enhanced the uptake of SO2. Transmission
electron microscopy (TEM) showed
that the particles broke up into smaller pieces after CP, and thus produced
more active sites. The “free-Fe” measurements confirmed that more reactive
Fe species were present after CP, which could enhance the SO2 uptake
more effectively. Mössbauer spectroscopy further revealed
that the formed Fe phases were amorphous Fe(III) and nanosized ferrihydrite
hybridized with Al / Si, which were possibly transformed from the Fe in the
aluminosilicate lattice. The modification of Fe speciation was driven by the
pH-dependent fluctuation coupling with Fe dissolution–precipitation
cycles repeatedly during the experiment. Considering both the enhanced SO2
uptake and subsequent promotion of iron dissolution along with more active
Fe formation, which in turn led to more SO2 uptake, it was proposed
that there may be a positive feedback between SO2 uptake and iron
mobilized on particle surfaces during CP, thereby affecting climate and
biogeochemical cycles. This self-amplifying mechanism generated on the
particle surfaces may also serve as the basis of high sulfate loading in
severe fog–haze events observed recently in China.
Introduction
Mineral dust is a major fraction of the global atmospheric aerosol budget, with
an estimated annual emission flux of 1000 to 3000 Tg into the atmosphere
(Jickells et al., 2005; Andreae and Rosenfeld, 2008). Mineral dust aerosol
mainly consists of quartz, feldspars, carbonates (calcite, dolomite) and
clay minerals (illite, kaolinite, chlorite, montmorillonite), the exact
composition varies with source (Claquin et al., 1999; Formenti et al., 2008;
Journet et al., 2008). A long-range transport would result in a decrease in
quartz relative to the clay fraction because of the more rapid removal of
quartz, hence clay is an important component of mineral dusts (Mahowald et
al., 2005; Journet et al., 2008). During the long-range transport, mineral
dust provides a reactive surface for heterogeneous chemistry (Zhang et al.,
2006; George et al., 2015; Huang et al., 2015). Heterogeneous reactions of
atmospheric trace gases on mineral dust particles are of great significance
as these reactions alter the chemical balance of the atmosphere and modify
the properties of individual particles (Usher et al., 2003; Wu et al., 2011;
Huang et al., 2015).
SO2 is an important trace gas, which is released mainly by fossil fuel
combustion and volcanic emission. The heterogeneous conversion of
SO2 on mineral dust surfaces leads to the formation of sulfuric acid
and sulfate aerosols, resulting in a significant cooling effect on the
global climate by scattering solar radiation and acting as cloud
condensation nuclei (CCN) to affect climate indirectly (Lelieveld and
Heintzenberg, 1992; Usher et al., 2003; Kolb et al., 2010). In addition,
sulfate-containing particles play a significant role in the haze formation
in China in recent years (Sun et al., 2014; Wang et al., 2014; Yang et al.,
2017). SO2 can be oxidized to sulfate by OH radical in the gas phase, be oxidation in cloud and fog droplets by ozone and hydrogen peroxide in the aqueous phase
(Luria and Sievering, 1991), or through heterogeneous processes that
occur on aerosol particle surfaces (Usher et al., 2003; Ullerstam et al.,
2003). However, the high sulfate levels measured in recent field
observations cannot be explained by current atmospheric models (Kerminen et
al., 2000; Wang et al., 2003; Cheng et al., 2016), leading to a large gap
between the modeled and field-observed sulfate concentrations using known
oxidation pathways (Herman, 1991; Kasibhatla et al., 1997; Barrie et al.,
2016). Overall, on a global scale, atmospheric SO2 concentrations were
typically overestimated, while sulfate tended to be underestimated,
suggesting missing sulfate production pathways (Harris et al., 2013; Kong et
al., 2014).
It has been suggested that the heterogeneous conversion of SO2 could
make an important contribution to the atmospheric sulfate loading.
Laboratory studies typically focus on SO2 uptake onto a variety of
metal oxides and mineral particles (Goodman et al., 2001; Usher et al.,
2002; Zhao et al., 2015; Yang et al., 2016) and have confirmed that its
conversion rate on the surface of Fe (hydr)oxides was faster compared to
other metal oxides investigated, in good agreement with the
field measurements (Usher et al., 2002; Zhang et al., 2006). Atmospheric Fe is emitted from both anthropogenic (primarily biomass
burning, coal and oil combustion) and natural (mineral dust and volcanic
ash) sources, with the mineral dust source dominant globally (Siefert et
al., 1998; Luo et al., 2008; Ito et al., 2019). It has been established that
an important in-cloud S(IV) oxidation pathway is catalyzed by natural
transition-metal ions, especially Fe hosted within mineral particles
(Alexander et al., 2009; Harris et al., 2013).
Another important consideration for heterogeneous chemistry of mineral dust
aerosol is how mineral dust particles change in the atmosphere. During
long-range transport, mineral particles often undergo chemical ageing by
atmospheric processes (Mahowald et al., 2005; Baker and Croot, 2010; Shi et
al., 2011). Cloud processing involves cloud water condensation and
evaporation on the particle surfaces, along with drastic liquid water
content and pH fluctuations (Mackie, 2005; Shi et al., 2011; Rubasinghege et
al., 2016). During cloud processing (CP), the high relative humidity (RH) results in
high aerosol water content and relatively high pH (Behra et al., 1989; Baker
and Croot, 2010; Shi et al., 2011). When water evaporates from
cloud droplets to wet aerosol at higher temperature, the particles only
contain a concentrated aqueous aerosol solution in which the pH can be
lower than 2 (Zhu et al., 1993; Meskhidze, 2003; Shi et al., 2015). Therefore, there is a highly acidic film (e.g., pH = 2) in the “wet
aerosol” phase versus a less acidic droplet (near neutral, 5–6) in the
“cloud droplet” phase within clouds (Shi et al., 2015). During its
lifetime, a typical aerosol particle may experience several cloud cycles
involving large pH variations before being removed from the atmosphere as
rain or through dry deposition (Pruppacher and Jaenicke, 1995; Maters et
al., 2016). Herein, the simulated CP experiment was conducted by
changing pH between 2 and 5–6, in accordance with the previous studies
(Spokes et al., 1994; Mackie, 2005; Shi et al., 2009).
It has been well documented that pH is especially important for Fe mobilization
(Zhu et al., 1993; Desboeufs et al., 2001; Deguillaume et al., 2010; Maters
et al., 2016). The fluctuating pH during CP will impact and change
the Fe speciation and morphology in dust particles (Zhuang et al., 1992;
Wurzler et al., 2000; Shi et al., 2009; Kadar et al., 2014). The low
pH will increase Fe solubility and bioavailability of dust during transport,
thereby providing Fe external input to the open ocean surface to promote
marine primary productivity (Spokes et al., 1994; Desboeufs et al., 2001). It
has been found that Fe-rich nanoparticle aggregates were formed from Saharan
soil and goethite upon simulated CP conditions, in good agreement with their
field measurements from the wet-deposited Saharan dusts collected from the
western Mediterranean (Shi et al., 2009). Fe nanoparticles are more
chemically reactive (Wurzler et al., 2000; Desboeufs et al., 2001), and possibly lead to a remarkable difference in heterogeneous chemistry.
However, little is known about the influence of CP on SO2 uptake onto
particle surfaces up to now.
In this study, we employed four typical Fe-containing mineral samples as
surrogates to perform simulated CP experiments. The SO2 uptakes on the
mineral particles before and after CP were compared using in situ diffuse
reflectance infrared Fourier transform spectroscopy (DRIFTS). Transmission
electron microscopy (TEM) was applied to observe the morphological and
mineralogical change of mineral particles. The Fe speciation modification
during simulated CP was further monitored by the dissolved Fe measurement,
the free-Fe analysis and Mössbauer spectroscopic characterization.
Materials and methodsMineral particles
The standard mineral samples of IMt-2, NAu-2 and SWy-2 were purchased from
the Source Clay Minerals Repository (Purdue University, West Lafayette, IN, USA).
ATD was purchased from Powder Technology Inc. (Burnsville, MN, USA). The
mineral samples were coarsely ground using a mortar and pestle before being
more finely ground using an all-dimensional planetary ball mill QM-QX
(Nanjing University Instrument Plant) and were sieved to particle diameters
(Dp) <45µm prior to analysis. The Brunauer–Emmett–Teller (BET)
specific surface areas (SBET) of the samples were measured with a
Quantachrome Nova 1200 BET apparatus. Total iron content (FeT) of the
samples was determined using inductively coupled plasma atomic emission
spectroscopy (ICP-AES, Jobin Yvon Ultima). The chemical compositions of the
particles were analyzed by X-ray fluorescence spectrometry (XRF, PANalytical
Axios Advanced).
Cloud processing simulation experiment
The simulated CP experiments were conducted at a constant temperature (298±1 K) using a Pyrex glass vessel with a water jacket. The suspensions
contained a mineral particle loading of 1 g L-1 and were subjected to
acidic (pH =2±0.1, 24 h) and near-neutral pH (pH = 5–6, 24 h)
cycles for one to three times according to the previous methods (Spokes et al., 1994;
Mackie, 2005; Shi et al., 2009). Suspension pH was adjusted by adding dilute
H2SO4 or NH4OH. The CaCO3 equivalent alkalinity of the
dust was determined in accordance with APHA (American Public Health Association) method 2320B so that acid
additions to control pH could be adjusted accordingly (Mackie, 2005). The
amount of acid or alkali added to achieve these pH cycles was less than
1 % of the total volume of the suspensions. The experiments were performed
under a constant stirring (about 50 rpm) in the dark for 144 h. At the end
of the CP experiment, the suspensions were filtered through 0.2 µm PTFE
filters (Millipore). The filter residue was air-dried and was further
applied to the DRIFTS experiment, as well as TEM observation, free-Fe
measurement and Mössbauer spectroscopic characterization.
SO2 uptake on the mineral particles
The SO2 uptake on the particle surfaces before and after CP was
investigated by a Shimadzu Tracer-100 FTIR spectrometer equipped with a
high-sensitivity mercury cadmium telluride (MCT) detector and a diffuse
reflectance accessory. A temperature controller was fitted to the DRIFTS
chamber to ensure constant reaction temperature (298 K). Weighted samples were
placed into a ceramic crucible (0.35 mm depth, 5 mm i.d.) in the chamber.
Mass flow controllers (Beijing Sevenstar electronics Co., LTD) were used to
adjust the reactant gases to a flux with expected concentration and relative
humidity. The sample was firstly pretreated in a 100 mL min-1 flow of
synthetic air (21 % O2 and 79 % N2) for 1 h to blow off water
and impurities on particle surfaces. When the background spectrum of the
fresh sample reached steady state, the reactant gas of SO2 (5.0 ppm)
along with synthetic air was introduced into the chamber at a total flow
rate of 120 mL min-1 for 45 min, during which the IR spectrum was
recorded automatically every 5 min at a resolution of 4 cm-1 for 100 scans in the spectral range of 900 to 4000 cm-1. Atmospheric moisture
was simulated with a RH level around 40 % by guiding one high-purity air
flux through water. The humidity value was monitored using a hygrometer.
The sulfate products were analyzed by ion chromatograph (IC) after the
DRIFTS experiments. The particles were extracted with 5 mL ultrapure water
by an ultrasonic extractor. After 10 min, the extracted solution was passed
through a 0.22 µm PTFE membrane filter and the leaching solution was analyzed
using a Metrohm 883 Basic IC equipped with an A5-250 column. A weak base
eluent (3.2 mmol L-1Na2CO3 plus 1.0 mmol L-1
NaHCO3) was used for anion detection at a flow rate of 0.70 mL min-1. To discriminate the adsorbed sulfate during simulated CP
experiment and the sulfate ions generated from the heterogeneous reaction,
the adsorbed sulfate on the particles during simulated CP experiment was
initially measured as blank. The heterogeneous uptake of SO2 was
calculated by subtracting the blank value from the total sulfate ions.
The reactive uptake coefficient (γ) was defined as the rate of
sulfate formation on the surface (dSO42-/dt, ions per second)
divided by collision frequency (Z, molecules per second) (Usher et al., 2003;
Ullerstam et al., 2003; Kong et al., 2014; Huang et al., 2015).
1γ=dSO42-/dtZ,2Z=14×As×SO2×v,3v=8RTπMSO2,
where As is the effective sample surface of the samples (m2), ν is the mean molecular velocity of SO2 (m s-1), R is the gas
constant (J mol K-1), T is the absolute temperature (K), and MSO2 is the molecular weight of SO2 (kg mol-1).
A conversion factor was obtained by a calibration plot with numbers of
SO42- analyzed by ion chromatography (IC, Metrohm
883 Basic, Switzerland) versus the integrated areas of sulfate products from
DRIFTS spectra. The residual sulfate during simulated CP experiments were
deducted as background. The calculated conversion factor of SO42- is 1.170×1015 (ions per integrated units). Integrated
areas for the total sulfur-containing products were calculated to show the
maximal sulfate formation rates. The reactive uptake coefficients for
SO2 were determined to be γBET and γgeo using the BET area (ABET= mass ×SBET) and
geometric area (Ageo= mass ×Sgeo) as the reactive
area, respectively.
Morphological and mineralogical characterization of the Fe speciation
A FEI TECNAI G2 S-TWIN F20 TEM equipped with an Oxford energy-dispersive
X-ray (EDX) spectrometer was used to analyze the morphological and chemical
composition of individual particles before and after CP. Suspensions (0.2 g L-1) of each particle were prepared in methanol and sonicated for at
least 1 h. A drop of this suspension was then applied to a carbon-coated Cu
TEM grid (400 mesh; EMS) and allowed to air-dry. The operation was conducted
in bright field mode at 120 kV. The Fe contents of the typical individual
mineral particle were calculated from the values of 50 typical particles. To
obviously observe the morphological changes, high-resolution TEM (HRTEM)
images were also collected to observe nanoscale structural features, e.g.,
surface roughness and lattice fringes.
The content of free Fe in the mineral particles was determined by a
citrate-buffered-dithionite (CBD) sequential Fe extractions method according
to the literature (Lafon et al., 2004; Shi et al., 2009). Simply, 30 mg of the dust samples was treated for 24 h with a 10 mL ascorbate solution
(pH = 7.5) to extract chemically highly labile Fe phases (FeA),
mainly composed of amorphous, nanoparticle and/or poorly crystalline
ferrihydrite. The solutions were filtered through 0.2 µm polycarbonate
filters. The dust particles collected on the filters were subsequently
treated for 2 h with a 10 mL sodium dithionite solution (pH = 4.8) to
extract crystalline Fe (oxyhydr)oxides (FeD), which are mainly
goethite and hematite. After each reaction step, the dissolved Fe
concentrations (FeA and FeD) in the filtrates were determined
using ICP-AES. The sum of these two pools (FeA+ FeD) was
defined as the “free-Fe” fraction (Shi et al., 2011). The other fraction
was denoted as the “structural-Fe” fraction in aluminosilicate crystals, which
could be calculated from the difference between the FeT and free-Fe
fractions (Lafon et al., 2004).
The Mössbauer spectroscopic analysis performed in transmission geometry
with a constant acceleration was used to inspect the chemical valence and
the surrounding structure of Fe in the particles before and after CP.
57Co was used as the Mössbauer source, and a 1 mm thick Na(TI) scintillator coupled to a EMI9750B photoelectric multiplier was
used as the detector (Cwiertny et al., 2008). The measurement was
carried out at room temperature (RT) with a duration of 24 h for one
sample (around 1.5×106 counts per channel). Experimental data
were fitted by a least-squares fitting program. The isomer shift values were
calibrated against a spectrum for α-Fe metal foil.
During the simulated CP experiment, the total dissolved iron (Fes) and
the dissolved Fe(II) in the suspensions were measured colorimetrically by
the ferrozine method, as described in previous studies (Viollier et al.,
2000; Cwiertny et al., 2008). For Fe(II) analysis, 200 mL of a 5 mM 1,10-phenanthroline solution and 200 mL of an ammonium acetate buffer were
added into 1 mL of sample. To avoid possible interference from Fe(III),
which can also form a complex with 1,10-phenanthroline when present at high
concentrations, 50 mL of 0.43 M ammonium fluoride was added to the sample
prior to 1,10-phenanthroline. The mixture was allowed to sit in the dark for
30 min prior to ultraviolet–visible spectroscopy (UV–Vis) analysis, during
which time a reddish-orange color developed if Fe(II) was present. Fes
was determined via the same protocol, except that 20 mL of 1.5 M
hydroquinone, which reduces Fe(III) to Fe(II), was added to the sample
rather than ammonium fluoride. Absorbance measured at 510 nm was converted
to concentrations using aqueous standards prepared from anhydrous beads of
ferrous chloride. Standards were prepared in each acid used in dissolution
studies, and no matrix effects were observed. These conditions resulted in a
detection limit of 1 µM. The concentration of dissolved Fe(III) was
calculated from the difference in experimentally measured concentrations of
total dissolved iron and dissolved Fe(II).
Additionally, the dissolved Fe(III) could precipitate out as the pH
increased, and then the Fe mineralogy of the deposit was also observed.
NAu-2 released about 300 µM of dissolved Fe at pH 2. The dissolving solution
(200 mL) was sampled after filtration (0.2 µm polycarbonate filter).
The clear solution was subjected to changing acidity from pH 2 to 5 by the
stepwise addition of dilute NH4OH. The precipitated particles were
separated out by 0.2 µm filters and were used in TEM and Mössbauer analysis. Size distributions for the Fe-bearing particles formed in
the suspensions were determined by a Horiba LB-500 light scattering
microscope within the size range of 3–6000 nm.
Results and discussionMorphological change of the mineral particles after CP
The characteristic results are shown in Tables S1 and S2 in the Supplement. The samples
exhibited SBET in the range from 4.3±0.3 to 22.6±2.3 m2 g-1. The FeT contents were 5.45±0.34 %, 26.30±0.57 %, 2.36±0.56 % and 1.48±0.56 % for IMt-2, NAu-2,
SWy-2 and ATD, respectively. The proportions of Fe2O3 in IMt-2,
NAu-2, SWy-2 and ATD were 7.95 %, 39.03 %, 5.55 % and 2.57 %,
respectively.
Figure 1 shows the TEM images of the mineral particles before and after CP.
As shown in Fig. 1a, c, e and g, the IMt-2, NAu-2, SWy-2 and ATD samples
before CP primarily consisted of laminar aluminosilicate with irregular
shape and rough morphologies mainly at the micrometer scale, all of which
were characterized by various fractions of Fe (1.5 %–26.2 %), along with
minor Mg (0.1 %–16.5 %), K (0.0 %–7.8 %) and Ca (0.0 %–1.1 %).
The Fe within the aluminosilicates of the particles was evenly distributed.
Besides, some Fe-rich crystals of several hundreds of nanometers in size
were found to attach onto the ATD particles, which were identified as
α-Fe2O3 from the typical d spacing analysis
of HRTEM (Janney et al., 2000).
After the simulated CP, all of the processed mineral particles showed much
smaller size than the ones before CP. For example, the typical IMt-2 and
NAu-2 particles after CP (Fig. 1b and d) were <1µm in size.
Under the TEM, the average Fe content of the individual IMt-2 and SWy-2
particles (Fig. 1b and f) decreased from 5.5 % (±1.9 %; n=50) to 4.1 % (±1.6 %; n=50) and from 2.4 % (±0.6 %;
n=50) to 2.1 % (±0.5 %; n=50), respectively. In addition,
the IMt-2 particles after CP showed a heterogeneous distribution of the Fe
on the basis of the EDX data. Most of the aluminosilicate in IMt-2 after CP
hosted lower Fe content (4.1 %), whereas a few of the Fe-rich particles
with less Si / Al were observed with irregular shapes at the nanoscale. The
TEM images of the NAu-2 and ATD particles after CP (Fig. 1h) showed some
pseudohexagonal nanoparticles with around 5 nm in diameter. Based on the EDX
and selected area electron diffraction (SAED) analysis, these nanoparticles were Fe-rich and the d spacings was at
about 1.5–2.5 Å, all of which were identified to be 2-line ferrihydrite
(Janney et al., 2000; Shi et al., 2009).
The TEM observation suggested that CP induced the disintegration of mineral
particles and thus produced enhanced surface area, resulting in more active
sites available on the particle surfaces for SO2 uptake. Results of TEM
also showed that CP influenced the Fe mineralogy and lead to the Fe-rich
nanoparticle formation, which could partly explain the higher SO2
uptake on the mineral particles after CP.
Comparison of morphologies and chemical properties for samples
collected before and after CP using TEM. The dotted circles indicate the
positions of the electron beam for the HRTEM images and SAED patterns.
Elements of the detected parts of individual particles are also presented.
Square brackets indicate mass percent of iron. The iron species were
identified by the Miller indices and the SAED patterns. (a) IMt-2 particles
characterized by high fractions of Al and Si, along with other crustal
elements including Mg, K and Fe. (b) IMt-2 particles after CP were almost
all less than 1 µm in size. Some Fe-rich particles with less Si and Al were
observed on the nanoscale dimension. (c) NAu-2 particles with high Fe / Si ratios
contain Mg, Al and Ca elements. (d) NAu-2 particles after CP were much
smaller than the ones before CP. Some ferrihydrite clusters were observed
and were attached on the surface of the NAu-2 particles after CP. (e) Typical SWy-2 particles were Al / Si rich, containing Fe, Mg and Ca elements.
(f) TEM images of the SWy-2 particles after CP appeared smaller than the
particles before CP. (g) The Si / Al-rich crystals in ATD particles were
aluminosilicate with a low content of Fe, and typical α-Fe2O3 particles were found to attach onto the
aluminosilicate surface. (h) The pseudohexagonal nanoparticles were observed
to on the surface of the α-Fe2O3 crystal among the ATD
particles. The SAED lattice constants of these nanoparticles were found to be
very close to that of 2-line ferrihydrite.
Effect of simulated CP on heterogeneous transformation of SO2
The in situ DRIFTS spectra on the IMt-2, NAu-2, SWy-2 and ATD samples before and
after CP exposed to SO2 as a function of time are shown in Fig. 2.
For the IMt-2 sample before CP (Fig. 2a and b), the intensities of the
broad peaks from 3600 to 3000 cm-1 and a weak peak at 1650 cm-1
increased with time. The band between 3600 and 3000 cm-1 was attributed
to the vibrations of hydrogen-bonded hydroxyl species (Zhao et al.,
2015), while the absorption peak at 1650 cm-1 was mainly
associated with H2O produced from the reaction between SO2 and
surface hydroxyls (Nanayakkara et al., 2012; Cheng et al., 2016). A
weak vibration was observed at around 1100 cm-1, which might be
attributed to free sulfate anions on the particle surface (Ullerstam et al.,
2003; Nanayakkara et al., 2012; Yang et al., 2016). Previous studies
established that various types of surface OH groups are the key reactive
sites for sulfite or sulfate and bisulfite or bisulfate formation on
mineral oxides (Faust et al., 1989; Usher et al., 2003; Ullerstam et al.,
2003), because of the complexes formed between sulfite or sulfate
species and the surface OH. Generally, the SO2 adsorption grows in
intensity with decreasing OH stretching and H2O banding (Zhang et al.,
2006). However, the OH peaks herein were not observed to decrease
with prolonged time because the losses of H2O and OH groups on the
particle surfaces were replenished by maintaining the constant RH in this
study.
Comparison of the DRIFT spectra of mineral dust samples upon
exposure to SO2 for 45 min before and after CP. Data for IMt-2 (a, b), NAu-2 (c, d), SWy-2 (e, f) and ATD (g, h) are shown in the ranges
of 4000 to 1250 cm-1 or 1250 to 1000 cm-1.
When the same set of experiments was carried out using the IMt-2 sample
after CP (Fig. 2b), the intensities of the prominent peaks were
significantly higher than those for the IMt-2 sample before CP. Four new
bands were readily observed at 1167, 1100, 1088 and 1077 cm-1. The new
bands were easily assigned to the stretching motion of surface-coordinated
sulfate species (1167 cm-1), i.e., bidentate surface sulfate complexes,
free sulfate ion (1100 cm-1), and sulfite or bisulfite species (1088 and
1077 cm-1) (Peak et al., 1999; Ullerstam et al., 2003; Yang et al.,
2016). These new bands remained when an argon blow-off process was
carried out, suggesting that the surface-adsorbed sulfite or sulfate species
between 1250 and 1000 cm-1 was chemisorbed (Zhang et al., 2006).
Upon adsorption of SO2 on the surface of the NAu-2 sample before CP
(Fig. 2c and d), the broad band from 3600 to 2800 cm-1 and the peaks
at 1580 and 1675 cm-1 increased drastically with time. These absorbance
bands were all attributed to the surface hydroxyl species (OH) and H2O.
No peaks were observed over the range of 1000 to 1250 cm-1, suggesting
that the sulfite or sulfate products were not newly formed on the surface of
the NAu-2 sample before CP. Upon adsorption of SO2 on the surface of
the NAu-2 sample after CP (Fig. 2d), the new bands at 3661 and 3450 cm-1, the broad band between 3400 and 2700 cm-1, and the broad
band centered at 2131 cm-1 were observed as the exposure time
increased. In detail, the band at 3661 cm-1 could be assigned to
stretching vibration modes of isolated or bridged surface hydroxyl groups
bonded to the surface iron ions embedded in the octahedral and tetrahedral
sites (Faust et al., 1989; Nanayakkara et al., 2012; Zhao et al.,
2015). The peaks at around 3450, 2131 cm-1 and the
band between 3400 and 2700 cm-1 were all attributed to surface OH
groups (Ma et al., 2010; Zhao et al., 2017). These new bands
generated on the processed NAu-2 particles suggested that CP changed the
location of diverse OH groups on the particle surfaces. Over the range of
1250–1000 cm-1, the new bands centered at 1170 cm-1 were assigned
to the asymmetric stretching of sulfate (Kong et al., 2014; Yang et al.,
2015).
The spectra of the SWy-2 samples before and after CP (Fig. 2e and f)
showed a similar spectral character with those of the NAu-2 samples. The
spectra for the ATD samples before and after CP (Fig. 2g and h) were
roughly the same as the ones for IMt-2. All of the results demonstrated that
the characteristic peaks for the active OH sites and the sulfite or sulfate
products on the mineral particles after CP were significantly higher than
those on the ones before CP, indicating the higher hygroscopicity and greater
SO2 uptake on the particles after CP. The data shown herein confirmed
that CP could potentially promote the transformation of SO2 on the
particle surfaces.
Comparison of the integrated areas on DRIFTS spectra in the range
of 1250–1000 cm-1 for the sulfate species formed on the samples before
and after CP.
Uptake coefficient of SO2 on the mineral particles before and after
CP
The areas of the bands (from 1250 to 1000 cm-1) attributed to the
sulfite or sulfate products as a function of time are shown in Fig. 3. It was
evident that the peak areas of the products on the mineral particles after
CP were generally greater than the ones before CP. The reaction on the
sample surfaces was practically saturated to SO2 uptake within 15 min,
except for the NAu-2 and IMt-2 samples after CP. As for all of the sample,
the saturation coverages of the sulfite or sulfate products after CP were
obviously greater than the corresponding values before CP, suggesting that
CP favored the sulfate formation on the mineral surfaces due to improving
active site number, as expected previously.
The maximum uptake coefficients (γgeo and γBET)
for SO2 uptake on the samples were estimated on the basis of the
sulfate formation rates in the initial 15 min. The values on the mineral
samples before and after CP are shown in Table 1. The γgeo
values of SO2 on the IMt-2, NAu-2, SWy-2 and ATD samples before CP were
1.03×10-7, 0.30×10-7, 1.72×10-7
and 1.37×10-7, respectively, which were in the order of
SWy-2, ATD, IMt-2 and NAu-2. The γgeo values of SO2 on the
IMt-2, NAu-2, SWy-2 and ATD samples after CP were 4.7, 19.4, 2.7 and 2.0
times higher than the values before CP, respectively, suggesting that the
SO2 uptake on the mineral particles significantly increased after CP.
Sulfate formation rates and uptake coefficients of SO2 on
particle samples before and after CP.
SamplesABETSulfate formationAgeometricγBETγgeometric(m2)rate (ions per second)(m2)(×10-12)(×10-7)(×1010)(×10-5)IMt-2 before CP0.7706.131.952.621.03IMt-2 after CP1.64028.721.955.764.85NAu-2 before CP0.7901.801.950.750.30NAu-2 after CP3.74934.571.953.065.83SWy-2 before CP0.90610.201.953.701.72SWy-2 after CP1.63127.191.955.494.59ATD before CP0.1668.111.9516.051.37ATD after CP0.24116.331.9522.332.76
ABET was more appropriate to represent the effective area because the
reactant may diffuse into tiny holes of the entire sample. The γBET values of SO2 on the IMt-2, NAu-2, SWy-2 and ATD samples
before CP were 2.62×10-12, 0.75×10-12,
3.70×10-12 and 1.61×10-11, respectively, which
were in the order of ATD, SWy-2, IMt-2 and NAu-2. It was noteworthy that the
SBET of samples increased after CP, as shown in Table 1. The γBET values of SO2 on the IMt-2, NAu-2, SWy-2 and ATD after CP
were 2.2, 4.1, 1.5 and 1.4 times higher than the values before CP,
respectively. The discrepancies in the γBET value confirmed
that the higher sulfate formation rates of the particles after CP were not
only due to the increased surface area of the particles but also resulting
from the chemical modification on the particle surfaces.
The estimated uptake coefficients were several orders of magnitude lower
than the results from Ullerstam et al. (2003) and Usher et al. (2003), which
could be partly explained by the difference in the preparation of mineral
dust samples or the difference between diverse experimental structures such
as the DRIFTS and Knudsen cell in kinetics discussion. In this study,
mineral dust particles were in a highly accumulative state in the sample
support of the Knudsen cell. The many layers of particles in the latter study
will hinder the diffusion of gas into the underlayer particles, resulting in
the underestimate of γBET. However, the values herein were
comparable to those obtained by the similar DRIFTS setup (Fu et al., 2007),
indicating the reliability of our measurements.
Comparison of the sulfate formation rates as a function of pH
cycle.
In addition, the formation rate of sulfate appeared as a linear increasing
trend as a function of pH cycles. Specifically, the increasing amount of
sulfate ions for the IMt-2, NAu-2, SWy-2 and ATD samples after each pH cycle
during CP were 7.0×1010, 1.0×1011,
5.0×1010, 3.0×1010 and in the order of NAu-2 > IMt-2 > SWy-2 > ATD (Fig. 4). The
multiple factors for γBET (γgeo) coincided
with the total Fe content of these samples: NAu-2 (26.30 %) > IMt-2 (5.45 %) > SWy-2 (2.36 %) > ATD (1.48 %).
We thus supposed that the SO2 uptake on these dust samples was closely
related to the Fe hosted in the particles.
The free-Fe (FeA and FeD) and
structural-Fe fractions were measured by the chemical CBD extractions for the
samples before and after CP. Results are present as relative percentage of
FeT.
Fe speciation analysis before and after CP
The free-Fe (including FeA and FeD) and
structural-Fe fractions in the mineral particles before and after CP were
determined by the CBD extraction (Fig. 5). In terms of total Fe, the
amorphous Fe (FeA) (e.g., nanoparticulate and poorly crystalline
ferrihydrite) contents of the IMt-2, NAu-2, SWy-2 and ATD samples before CP
were 0.7 %, 0.5 %, 0.7 % and 3.8 %, respectively. The crystalline Fe
(oxyhydr)oxides (FeD) (e.g., α-FeOOH and α-Fe2O3) contents of the IMt-2, NAu-2, SWy-2 and ATD samples
before CP were 7.2 %, 2.3 %, 4.5 % and 35.5 %, respectively. As a
result, the structural-Fe fractions before CP were 92.1 %,
97.2 %, 94.8 % and 60.7 %, respectively, for IMt-2, NAu-2, SWy-2 and
ATD.
After CP, the FeA contents of the IMt-2, NAu-2, SWy-2 and ATD samples
reached 1.8 %, 1.2 %, 1.7 % and 24.2 %, respectively, which
increased by 2.6, 2.4, 2.4 and 6.4 times as compared to the ones before CP.
The crystalline Fe (oxyhydr)oxides (FeD) contents of the samples after
CP were not significantly changed as compared to the ones before CP, whereas
the contents of the structural-Fe fraction in the Al-Si crystals of the IMt-2, NAu-2,
SWy-2 and ATD samples after CP decreased by various degrees to 91.1 %,
96.1 %, 93.2 % and 42.5 %, respectively. Previous research had
indicated that FeA increased as a result of the simulated CP (Shi et
al., 2009). Herein, we further proposed that the increased fractions of
FeA could be mostly transformed from the structural-Fe fraction in the
aluminosilicate phase of the particles during CP, which is in good agreement
with the TEM observation. For example, the FeA in the ATD samples
increased from 3.8 % to 24.2 % after CP, accompanied by a sharp decrease
in the structural-Fe content from 60.7 % to 42.5 %.
Mössbauer spectroscopy measured for samples. IMt-2 before and
after CP (a, b), NAu-2 before and after CP (c, d), SWy-2 before and
after CP (e, f), ATD before and after CP (g, h). Experimental data
were fit using a least-squares fitting program. The IS values were relative
to α-Fe at RT. Prominent spectral features associated with different
iron species are indicated.
The Mössbauer spectra and their fitted results are shown in Fig. 6.
The corresponding hyperfine parameters estimated from the best fitted
spectra are presented in Table S3. The central doublet with isomer shift
(IS) of 0.37 mm s-1 and quadrupole shift (QS) of 0.72 mm s-1 were
typical for high-spin Fe(III) in octahedral symmetry (Eyre and Dickson,
1995), while the other one with IS of 1.12 mm s-1 and QS of 2.65 mm s-1 was characteristic of high-spin Fe(II) (Hofstetter et al., 2003;
Kopcewicz et al., 2015). The two doublet components of the IMt-2,
NAu-2, SWy-2 and ATD samples before CP were all attributed to different
fractions of Fe(III) and Fe(II) in the aluminosilicate crystals. Before CP, the Fe(II) fraction in the IMt-2, NAu-2, SWy-2 and
ATD samples were 34.0 %, 12.9 %, 18.3 % and 29.0 %, respectively
(Fig. 6a, c, e and g). Furthermore, the spectra of the ATD sample before
CP showed not only two central quadrupole doublets but also one MHS (magnetic hyperfine splitting) sextet
with IS of 0.39 mm s-1, QS of -0.13 mm s-1 and Hf of 51.1 T. The MHS sextet, which shared 31.8 % of the whole area, could be
ascribed to α-Fe2O3 (Kopcewicz and Kopcewicz, 1991), in agreement with the TEM analysis and free-Fe measurement
as mentioned previously.
The concentrations of Fes, dissolved Fe(II) and Fe(III) in
the suspensions measured over 144 h in the solution cycled between pH 2 and
pH 5 for IMt-2 (a), NAu-2 (b), SWy-2 (c) and ATD (d), respectively.
After CP, the Fe(II) contents of the samples decreased to 31.5 %, 11.6 %, 17.1 % and 10.9 %, respectively, for IMt-2, NAu-2, SWy-2 and ATD
(Fig. 6b, d, f and h). It was supposed that the Fe(II) release is more
energetically favorable than the one of Fe(III) due to the bond strength. As to
the ATD sample after CP (Fig. 6h), not only did the Fe(II) fraction
decrease from 29.0 % to 10.9 % but the Fe(III) fraction in the
aluminosilicates also decreased from 39.0 % to 33.0 %. Meanwhile, the α-Fe2O3 fraction was not significantly changed (31.8 % vs. 32.3 %). As discussed previously, the Fe mobilization was dependent on the
specific chemical bonds. The FeD phase in α-Fe2O3
with the strong FeO bond was less liable than that embedded in the
aluminosilicate lattice (Strehlau et al., 2017). It has been well
documented that the Fe replacing alkaline elements as the interlayer ions
was easily mobilized compared to the Fe bound by covalent bonds in the
aluminosilicate matrix (Luo et al., 2005; Cwiertny et al., 2008; Journet et
al., 2008). Therefore, the Fe in the aluminosilicate fraction of the
mineral particles exhibited varied iron solubility.
TEM images of the newly formed particles in the precipitation
experiment. Based on the TEM-EDX measurement and SAED analysis, these
particles could be categorized into two different types, which are circled
in (a). The typical sizes of the first type were hundreds of
nanometers. The enlarged images are displayed in (b, c, d). The
insert EDX data and SAED image confirmed that they were poorly crystalline
aluminosilicate with low Fe but high Si / Al contents. The second particle type (e, f, g) was Fe rich but with a lower amount of Si / Al, which was nearly
1 µm in size. Based on the EDX data and the SAED analysis, these
bigger particles were ambiguously identified as
Na0.42Fe3Al6B309Si6O18(OH)3.65.
Particularly, a new quadrupole doublet with IS of 0.67 mm s-1 and QS of
1.21 mm s-1 was observed in the spectra of the ATD sample after CP
(Fig. 6h), which shared 23.8 % of the total area, and was possibly
indicative of the Fe(III) oxide hybridized in the aluminosilicate matrix
(Kopcewicz and Kopcewicz, 1991). The free-Fe measurements have
indicated that the FeA fraction of ATD increased by 20.4 % after CP,
so this Fe phase was most likely an amorphous Fe(III) hybridized
with Al / Si. In terms of the other samples after CP, the magnetic signal
of the newly formed Fe(III) phase was not detected. This was probably due to the fact that the newly formed Fe fractions were not available at sufficiently high levels
to be clearly resolved by the Mössbauer spectroscopy method, and/or the slight
signal drift and the poor signal-to-noise ratio made an unambiguous
identification difficult. Herein, the newly formed amorphous Fe(III) phase
was supposed to be a reactive Fe-bearing component, which may contribute
significantly to the SO2 uptake even at a low level.
Mössbauer spectroscopy measured at RT for the newly formed
particles collected in the precipitation experiment.
The dissolution–precipitation cycle of the mineral Fe during CP
During the simulated CP experiments, the concentrations of total dissolved
Fe (Fes), dissolved Fe(II) and Fe(III) released from the particles, as a
function of time are shown in Fig. 7. Similar dissolution trends were
observed for all of the samples. One can see that the suspensions at pH 2
induced a rapid increase in Fes. Increasing the pH from 2 to 5
resulted in a rapid and almost complete removal of Fes. In fact, only a
rather small fraction of the Fe in dusts could be dissolved at pH values above 4
(Zuo and Hoigne, 1992). The dissolved Fe precipitated rapidly as
an insoluble deposit at pH 5. When the suspension pH was again reduced to 2, a
steep increase in the Fes concentration was measured once again. The
fast Fe release was due to the redissolution of the Fe-rich precipitates,
which was proposed to be reactive Fe phases (Shi et al., 2009,
2015). Such highly soluble Fe-bearing precipitates have been observed under
the TEM, as well as the free-Fe measurement and Mössbauer
characterization.
For each pH cycle during the simulated CP experiment, the overall changes in
total released Fe concentrations were reproducible. The Fe ion on the
particle surfaces would experience a continuous process of dissolution, precipitation, redissolution and reprecipitation when the pH
cycles between pH 2 and pH 5 (cloud-aerosol modes). During this process, the
Fe(II) fraction would be transformed to Fe(III). The results shown herein
suggest that CP could significantly modify Fe partitioning between
dissolved and particulate phases in the real atmosphere. Not only did the
increase in specific surface area contribute to the enhanced sulfate
formation but the highly reactive Fe on the particle surfaces yielded
during CP were also responsible for the higher SO2 uptake on the
particles after CP.
When investigating the NAu-2 sample, once the pH of the clear solution
increased from 2 to 5–6, the Fe-bearing nanoparticles separated out from the
solution rapidly and precipitate out slowly. The sample developed an initial yellow
color and then an orange colored suspension. The TEM images of the
precipitated particles are shown in Fig. 8. The particles could be
categorized into two different types. One type of particle could be
characterized as hundreds of nanometers in size, with low Fe but high Si / Al
content. The other type displayed particle sizes of nearly 1 µm and
were Fe rich but contained a smaller amount of Si / Al components. These
bigger particles were ambiguously identified as
Na0.42Fe3Al6B309Si6O18(OH)3.65 on the basis of the EDX data and SAED analysis. It is likely that
the Al / Si elements also precipitated out along with the Fe.
The Mössbauer spectra of the precipitated Fe-rich particles are shown in
Fig. 9. Two central doublets were distinguished: one (48.4 %) of IS = 0.45 mm s-1 and QS = 0.75 mm s-1 and the other (51.6 %) of
IS = 0.24 mm s-1 and QS = 0.76 mm s-1. Both of the two doublet
components could be attributed to the Fe(III) fraction in the
aluminosilicates (Kopcewicz et al., 2015). The results were in good
agreement with the TEM observation, which showed that most of these Fe
particles were mostly present as the Fe(III) hybridized with Al / Si. The
particle size distributions in the suspensions were also determined by
dynamic light scattering, as shown in Fig. 10. When pH was lower than 2.0,
the particles seemed to stabilize below 10 nm in size. These Fe colloids
were thought to be a source of soluble Fe (Janney et al., 2000). Once pH increased, the size of precipitated particles quickly increased,
even to the microscale, and the suspension was featured with a polydispersed
size distribution.
Conclusively, the precipitated Fe particles were mainly Fe(III) with weak crystal
structure and/or ferrihydrite nanoparticles hybridized with Al / Si, which were
possibly transformed from the Fe hosted in the aluminosilicate matrix of the
particles. The particle surfaces after CP were coated by these reactive Fe
to provide more surface OH species, resulting in enhanced SO2 uptake.
During the precipitation experiment, the particle size
distributions in the suspensions were determined by dynamic light
scattering. The presented size distributions are characteristic of
newly formed nanoparticles or microparticles as the suspension pH raised from
1.0 to 3.8.
Conclusion and implication
Transition metal ions, especially Fe(III), can catalyze SO2 oxidation
rapidly in cloud drops (Harris et al., 2013). This study further confirmed
that SO2 uptake on the mineral particles could be greatly enhanced by
CP, possibly more than described previously. The higher uptake
coefficient of the particles after CP was not only due to increased
surface area but also resulted from the chemical modification of the
particle surfaces. The free-Fe and Mössbauer analyses
suggested that CP triggered new formation of amorphous Fe particles on the
surfaces, which were mostly transformed from the Fe hosted in the
aluminosilicate matrix. TEM showed that the amorphous Fe(III) and/or
ferrihydrite nanoparticles were hybridized with Al / Si. In general, the
acidity fluctuation during CP enables the dissolution–precipitation cycles
of mineral Fe to yielded more reactive Fe, resulting in more SO2 uptake
on the particle surfaces. More SO2 adsorption further increases the
surface acidity of dust particles, in turn leading to higher Fe solubility;
again, more sulfate formation. It was thus proposed that there is a positive
feedback relative to SO2 uptake and iron mobilized from mineral
particles during CP, therefore enhanced sulfate formation greatly.
Our results also serve to explain high sulfate loading in fog–haze episodes
of China. It has been recommended that sulfate contributed significantly to
the explosive growth of fine particles, thus exacerbating severe fog–haze
development (Kasibhatla et al., 1997; Nie et al., 2014; Barrie et al.,
2016). Haze and fog within an episode was often found to transform each
other at a short time due to the diurnal variation in RH, whereby the
haze-fog transition was probably analogous to the aerosol–cloud interaction.
Water content of aerosol or fog drops was regulated by RH, and thus allowed
the particle acidity fluctuation. Although the aerosol acidity could
not be accurately determined from field measurements or calculated using the
thermodynamic model, we recognized that the large pH fluctuations between
the haze-fog modes could significantly modify the microphysical properties
of mineral particles, trigger formation of reactive Fe particles and thus accelerate sulfate formation via a self-amplifying
process, contributing to explosive growth of fine particles at the initial
stage of fog–haze events. The data presented herein also highlight that CP
provides more bioavailable iron from mineral particles than one expected
previously, which is a key speciation to promote oceanic primary
productivity. Results of this study could partly explain the missing source
of sulfate and improve agreement between models and field observations.
Additionally, previous studies indicated that Fe in pyrogenic aerosols was
always presented as liable Fe, such as ferric sulfate and aggregated
nanocrystals of magnetite (Fe3O4) (Fu et al., 2012), and displayed
higher Fe solubility compared to dust (Desboeufs et al., 2005; Sedwick et
al., 2007; Ito et al., 2019). Alexander et al. (2009) demonstrated that the sulfate
formed through metal catalysis was highest over the polluted industrial
regions of northern Eurasia, suggesting that the increasing importance of
the metal-catalyzed S(IV) oxidation pathway due to anthropogenic emissions
(Alexander et al., 2009). With the rapid development of industry and
agriculture, the pyrogenic Fe-containing aerosols are indispensable
contributors to the atmospheric Fe load in China. Thus, the acidic solution
at pH 2 and high sulfate loading of fine particles in severe fog–haze events
of China might be more relevant to Fe-containing combustion aerosols than
mineral dust. Based on the current findings, not only the potential
influences of cloud liquid water content, light and organic ligands but
also the solubility and speciation of Fe in pyrogenic aerosols will be
considered during the simulated CP experiments in the future. A more
detailed understanding of the iron–sulfur cycle during CP is therefore
critical to estimate accurately the contribution of CP to global sulfate
loading and its impact on the climate.
Data availability
All data described in this study are available upon request from the corresponding authors.
The supplement related to this article is available online at: https://doi.org/10.5194/acp-19-12569-2019-supplement.
Author contributions
ZW, HF and JC designed the experiments. ZW, TW, HF and LZ
performed the laboratory experiments. HF, JC, LZ and VG contributed
reagents and analytic tools. CG, VG and MT gave some valuable suggestions
in designing the experiments. ZW, TW and HF analyzed data. ZW and
HF wrote the article with inputs from all coauthors.
Competing interests
The authors declare that they have no conflict of interest.
Special issue statement
This article is part of the special issue “Multiphase chemistry of secondary aerosol formation under severe haze”. It is not associated with a conference.
Acknowledgements
This work was supported by the National Natural Science Foundation of China
(nos. 91744205, 21777025, 21577022, 21177026), the National Key R&D Program
of China (2016YFC0202700), and the Opening Project of Shanghai Key Laboratory of
Atmospheric Particle Pollution and Prevention.
Financial support
This research has been supported by the National Key R&D Program of China (grant no. 2016YFC0202700), the National Natural Science Foundation of China (grant nos. 91744205, 21777025, 21577022, 21177026), the International Cooperation Project of Shanghai Municipal Government (grant no. 15520711200), and the Opening Project of Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (grant no. 46685365).
Review statement
This paper was edited by Hang Su and reviewed by two anonymous referees.
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