Introduction
Volatile organic compounds (VOCs) are widely recognized as playing a critical role
in atmospheric chemistry and climate, because of their important impact on
the atmospheric oxidation capacity and contribution to the formation of
secondary organic aerosols (SOAs) (Andreae and Crutzen, 1997; Atkinson, 2000;
Fuentes et al., 2000; Williams, 2004; Tunved et al., 2006; Lelieveld et al.,
2008; Zhang et al., 2008; Pöschl et al., 2010), and VOCs adsorbed on
aerosol particles can have severe health implications (Glikson et al., 1995;
Pöschl, 2005). The main sources of VOCs include the biosphere, biomass
burning and anthropogenic activities, with emissions from the biosphere
accounting for ∼90 % of global total atmospheric VOCs (Guenther et
al., 1995). Once VOCs are emitted, they can be removed from the atmosphere by
either direct wet or dry deposition to various surfaces including vegetation
and soil (130–270 Tg C yr-1), or be transformed into SOAs
(510–910 Tg C yr-1), or be oxidized ultimately leading to the
formation of CO2 and H2O (310–720 Tg C yr-1)
(Goldstein and Galbally, 2007). The reported discrepancies between field
observations and model calculations, however, indicate that many potential
sources and sinks still need to be identified and quantified (Di Carlo et
al., 2004; Heald et al., 2005; Volkamer et al., 2006; Goldstein and Galbally,
2007; Warneck and Williams, 2012).
Biogenic VOC emission from vegetation has long been the major focus of VOC
exchange studies (e.g., Guenther et al., 1994; Gershenzon, 1994; Fuentes et
al., 1996; Fall et al., 1999; Schade and Goldstein, 2002). Early studies
presumed that vegetation only emitted VOCs to the air. However, more recent
studies have demonstrated that VOC exchange is bidirectional, and uptake of
VOCs and their oxidation products are the rule rather than the exception in
many cases (Kesselmeier, 2001; Fares et al., 2015; Guenther, 2015; Cappellin
et al., 2017; Karl et al., 2005, 2010; Seco et al., 2007; Park et al., 2013;
Gordon et al., 2014a; Niinemets et al., 2014), similar to other trace gases
such as NH3 or HONO (Su et al., 2011, 2013). In fact, Park et al. (2013)
expanded the number of measured VOC species to an extremely large range,
covering 555 ions (with mass to charge ratios between 31 to 1263) using
high-mass-resolution proton-transfer-reaction mass spectrometry over an
orange plantation and found that 494 of the VOC species showed bidirectional
fluxes and 186 even exhibited net deposition.
Compared to the research effort dedicated to atmosphere–vegetation
interactions involving VOCs, the exchange between the atmosphere and soils
has received relatively little attention (Lamb et al., 1987; Guenther et al.,
1995; Asensio et al., 2008). Soils have been characterized as both a source
and a sink for VOCs. Soil emissions of short-chain oxygenated VOCs (e.g.,
methanol, acetaldehyde and acetone) and terpenes have been observed in
previous studies (Warneke et al., 1999; Schade and Goldstein, 2001; Hayward
et al., 2001; Schade and Custer, 2004; Lin et al., 2007; Gray et al., 2014;
Bourtsoukidis et al., 2018). In contrast, some species including alcohols,
aldehydes, ketones, aromatic hydrocarbons, isoprene, monoterpenes and
hexenal, etc. have been reported to be deposited on various types of soil in
other studies (Asensio et al., 2007a, b, 2008; Aaltonen et al., 2013; Gray et
al., 2014). Previous laboratory measurements have also indicated that soil
could serve as a temporary reservoir for formaldehyde, i.e., a large fraction
(∼70 %) of formaldehyde adsorbed by soil at high mixing ratios could
be re-emitted into the atmosphere at low ambient conditions; hence
formaldehyde could cycle between the atmosphere and soil (Li et al., 2016).
VOC emission from ground level can originate from the overlying soil litter
(Gray et al., 2010; Warneke et al., 1999; Hayward et al., 2001; Schade and
Goldstein, 2001), roots (Janson, 1993; Chen et al., 2004; Lin et al., 2007)
and soil-dwelling microorganisms (Scholler et al., 2002), for which the
relative contributions depend on the soil type and various environmental
parameters such as ambient relative humidity (RH), soil water content,
temperature (T), and VOC mixing ratio, etc. Therefore, VOC formation from
soils involves both biotic and abiotic mechanisms. The biotic processes
include root exudation and degradation of soil organic
matter and leaf litter by soil microorganisms. The abiotic mechanisms involve
purely physicochemical reactions (e.g., heterogeneous and multiphase
transformation, evaporation, desorption) and UV-light-enhanced emission from
soil vegetation or decomposition of leaf litter (Niemi et al., 2002; Rinnan
et al., 2003; Zepp et al., 2007; Derendorp et al., 2011). The main mechanisms
contributing to the uptake of VOCs were reported to include adsorption and
degradation by roots (Simonich and Hites, 1995; Newman et al., 1997; Cho et
al., 2005), biodegradation by microorganisms (van Roon et al., 2005) and
physical/chemical adsorption by soil particles (Pignatello and Xing, 1996; Li
et al., 2016).
Thus, both biotic and abiotic mechanisms can contribute to the exchange of
VOCs on soils. Under real-world
conditions, the biotic and abiotic processes on soil are highly coupled and
the net flux is the result of many complex multiphase interactions that are
difficult to resolve. Furthermore, emissions from the soil may be taken up or
transformed in overlying leaf litter. Resolving the key processes requires
the system to be examined in separate components. Here, by applying a new
reactor system, we examine the physicochemical effects of soil on VOC
exchange in isolation, but under real-world conditions. From the perspective
of soil physicochemistry, VOCs can undergo reversible adsorption and
irreversible surface reactions on soils and aerosol particles, coupling
gas–surface transport (adsorption), surface-bulk transport
(absorption/solvation), and chemical reactions in bulk (Pöschl et al.,
2007); and VOC oxidation/decomposition products can desorb immediately or
further interfere with other reactants (Ammann and Pöschl, 2007).
Heterogeneous processes at the gas–surface interface can be highly complex,
and the individual steps controlling the reaction rates of heterogeneous
processes are rarely known (Crowley et al., 2010; Chapleski et al., 2016).
Parameterizations of heterogeneous processes still tend to be empirical and
most are untested in natural outdoor settings, where surfaces are prone to
interference from competitively co-adsorbing trace gas species and radicals,
which is specifically crucial in the case of reactive trace gases like VOCs.
While laboratory-based trace gas uptake studies normally apply individual VOC
species separately, only little attention is given to interfering effects.
However, laboratory studies on binary organic compound mixtures in the
parts-per-million (ppm) level have shown that the photocatalytic oxidation on catalytic
surfaces (TiO2) of one VOC species may promote or inhibit the
oxidation rate of another (Lichtin et al., 1996). In contrast to laboratory
conditions, ambient air is a complex composite of a vast variety of gases,
aerosols and radicals, and some components may exert synergistic effects on
the heterogeneous chemistry of individual or categories of VOC species.
Neglecting these synergistic effects may cause misleading results when
extrapolating laboratory work to real-world conditions.
This study aims to investigate the uptake, potential heterogeneous conversion
and emission of VOCs on soil under
real-world ambient conditions. A flow tube system coated with pretreated
sterilized soil was used to investigate the physicochemical background of VOC
exchange on soil independently from
biological activity. Recently, the flow tube technique has been adopted to
study the kinetics and mechanisms of reactive trace gas uptake onto soils
(Wang et al., 2012; Donaldson et al., 2014a, b; VandenBoer et al., 2015; Li
et al., 2016). These investigations, however, have focused on laboratory
experiments under controlled environmental conditions, where the dependence
on individual relevant parameters was investigated while all others were kept
constant. Here, the coated-wall flow tube system was deployed at an urban
field site, which allowed ambient air to pass through the flow tube and the
coated soil sample to interact directly with ambient VOC species. VOC uptake
coefficients (γ), which indicate the fraction of trace gas kinetic
collisions with a reactive surface that lead to uptake by the surface (Ammann
et al., 2013), are determined, and their dependencies on various
environmental parameters are discussed. To the best of our knowledge, this is
the first trial to deploy the flow tube technique for field observations to
investigate uptake/emission kinetics of VOCs on soil under ambient conditions.
Methods
Soil sample preparation
Soil samples were collected from a scrubland site near Weiminghu Lake in
Peking University, Beijing, China (39∘59′ N, 116∘18′ E). Before
collection, leaf litter was removed from the ground surface and soil
particles were only obtained at a depth of 0–5 cm. The collected samples
were air-dried in a shaded place prior to grinding and sieving with a
120 mesh soil sieve. The soil pH was
∼6.8 (1:2 soil/water (v/v), Thermo Scientific, OrionStar A211 pH
meter). The soil texture comprised of 49 % sand, 35 % silt and
16 % clay (wet sieving method) and the soil humus content was 8.8 %
(loss on ignition method) as analyzed by Guangdong Institute of
Eco-environmental and Soil Sciences (Guangzhou, China). Since the purpose of
this study was to investigate the physicochemical interactions between VOCs
and soil, the sieved soil was autoclaved for 20 min at 394 K (repeated
twice with an incubation time of 1 day) right before the flow tube coating
procedure as in the work of Li et al. (2016). Autoclaving has been reported
as the most effective sterilization method for eliminating soil
microorganisms compared with other methods such as fumigation, UV and
microwave irradiation (Razavi darbar and Lakzian, 2007). The sterilization
procedure and the autoclave time eliminated primary microbial impact on VOC
exchange at the atmosphere–soil interface and minimized potential influence
on soil physicochemical properties caused by the sterilization method itself
(Berns et al., 2008). Moreover, a PTFE membrane filter installed
upstream of the flow tube system could prevent the bacteria in the ambient
air from inhabiting the soil sample during the field measurement (see
Sect. 2.2).
Soil slurry was prepared by mixing dry soil with sterilized deionized water
(18.2 MΩ cm; Millipore Corporation, Darmstadt, Germany). The slurry
was uniformly injected into a glass tube with a sandblasted inner surface
(100 mm length, 17 mm ID), which was then installed into an air-dried
continuously rotating coating tool (ACRO). The design and performance of ACRO
for soil coating had been described in the work of Li et al. (2016). The
coated tube was rotated with a speed of 14 rpm and flushed overnight with
pure N2 at a flow rate of ∼0.5 L min-1
(purity ≥ 99.999 %, RH = 0 %). Note that the drying process
with N2, to some extent, purges VOCs off the soil sample. The
coating mass has been shown to affect the gas uptake (Donaldson et al.,
2014a; Li et al., 2016). A relatively large coating mass of
∼95 mg cm-2 (corresponding to a geometric coating thickness
∼500 µm) was chosen for our experiments. The coating procedure
and mass has been experimentally shown to guarantee fair homogeneity and
reproducibility of the coating in our previous study (Li et al., 2016).
Prior to the VOC exchange experiment under ambient conditions, the freshly
coated tube was flushed with N2 (purity ≥ 99.999 %,
RH = 0 %) for 40 min to scrub potential VOC impurities from the soil
which were either adsorbed onto or absorbed into the soil during the coating
preparation procedure or from the soil coating itself. Note
that during flushing with VOC-free N2, many VOC species were indeed
emitted (Fig. S1 in the Supplement). These emitted VOC species might
originate from the soil surface and/or the soil bulk (including soil
particles and residues of the autoclaved microorganisms) through pore
diffusion. To quantify the soil layer depth contributing to these observed
emissions, the desorption curves (in Fig. S1 in the Supplement) were fitted
using the function derived in our previous study (the first function in
Table 1 in Li et al., 2016) assuming that the emissions were a first-order
decay process. The determined desorption rate coefficient and desorption
lifetime of the detected VOCs are listed in Table S1 in the Supplement. The
longest desorption lifetime is found for formaldehyde as ∼22 min.
Moreover, we estimated the timescale t for a VOC molecule diffusing through
the entire soil coating thickness δg
(∼500 µm) using equation t=δg2/Da,
where Da is the macroscopic diffusion coefficient of VOCs within soil
pores. Adopting the lower limit of a macroscopic diffusion coefficient which
typically ranges 10-4–10-2 cm2 min-1 for clay minerals
reported by Morrissey and Grismer (1999), a VOC diffusion time of
∼25 min was obtained. This timescale is less than or comparable to our
flushing time of 40 min, suggesting that the entire soil layer could
contribute to the VOC emissions by means of soil surface desorption/reaction
and soil bulk pore diffusion. In addition, the amount of soil-emitted VOCs
was estimated by integration of the desorption curve of methanol (which shows
the highest emission signals, an order of magnitude higher than the others in
Fig. S1 in the Supplement) using the fitting functions derived by Li et
al. (2016). The emitted methanol mass is ∼1.71 µg, which is
far from being able to account for a monolayer coverage on the specific soil
layer surface (see Sect. 2.3) when assuming an effective diameter of the
methanol molecule of 4.2 Å according to Perera et al. (2007). Thus, the
flushing procedure could provide adsorption sites devoid of reversibly
absorbed VOCs on the soil surface as well as within the soil pores and
therefore allow a focus on uptake kinetics from the initial phase (VOC-free
soil) of the exchange experiment.
Measurement site, experimental setup and operation
VOC exchange measurements were conducted within the campus of Tsinghua
University, Beijing, China (40∘ N,
116∘12′ E), from 25 August to 26 September 2015. This urban background
site was 200 m east of a four-lane highway and 100 m west of a garbage
station. There was a small mound nearby which was covered by grassland mixed
with trees (mainly white poplars) on its northern side.
The aim of this study was to investigate VOC exchange at the atmosphere–soil
interface under ambient conditions, where air temperature, relative humidity and VOC mixing ratio, etc. all
change in concert. A flow tube system was installed in a self-built sampling
box, which was located on the roof of a 2.35 m high storage container. Two
openings on the sampling box allowed for direct access of ambient air into
the flow tube system. The sampling box was covered with a thin nontransparent
PTFE film (coated with an aluminium foil and with a total thickness of
∼0.5 mm) that functioned as both a reflector for sunlight and a shelter
from rainwater. The flow tube system consisted of a sample channel and a
reference channel. The sample channel was equipped with a soil-coated tube in
front of which a pretube or entrance region (with the same dimensions as the
soil-coated tube, i.e., 100 mm length, 17 mm ID, but without soil coating)
was installed to ensure well-developed laminar flow in the soil-coated part
(Li et al., 2018). The reference channel used a 0.25 in. (i.e., 6.35 mm OD)
PFA Teflon tube (200 mm length) without coated soil. As shown in Fig. 1,
ambient air was introduced into the flow tube system prior to being analyzed
by a proton-transfer-reaction mass spectrometer (PTR-MS). By using solenoid
valves, VOCs from the sample and reference channels were alternately analyzed
by the PTR-MS (with 60 min for each channel). While one channel was
connected with the PTR-MS, the other was simultaneously flushed by ambient
air with the same flow rate as that of the PTR-MS (∼0.1 L min-1)
to prevent potential accumulation/depletion of VOCs under otherwise static
conditions. PTR-MS analysis was paused on 4–8 September 2015, but the flow
tube was continuously flushed with ambient air to ensure uninterrupted
exposure of the soil sample to dynamic ambient conditions.
Schematic illustration of the experimental setup.
When the reference channel was connected to the PTR-MS, the detected VOC
signals represented their mixing ratios in ambient air (VOC depletion within
the PFA Teflon tube was negligible), denoted as Cr, which was
also equal to the VOC mixing ratios at the sample tube inlet. When the sample
channel was connected, the detected signals represented the VOC mixing ratios
subject to interactions with the coated soil, designated as Cs.
Considering the short residence time (∼24 s) within the sample tube
volume, gas-phase-reaction-induced depletion of VOCs only accounted for a
small fraction (∼3 % for very
reactive species like isoprene and much less for the others, estimated based
on the measured gas oxidants mixing ratios (see Sect. 3.1) and assuming a
background mixing ratio level of 1 ppt for OH radicals). Thus, the VOC
mixing ratio difference between the reference channel and the sample channel,
Cr–Cs, can be assumed to be mainly due to exchange
of VOCs on soil. Note that the
PTR-MS could not detect Cr and Cs simultaneously;
when one channel was connected to the PTR-MS the corresponding VOC mixing
ratios of the other were determined afterwards by interpolating the adjacent
measured values. Before the start of field measurements, a PTFE membrane
filter (Φ: 50 mm, pore size: 0.2 µm; Millipore Corporation,
USA) was installed at the air inlet of the VOC exchange system to filter
bacteria as well as other particles in the ambient air. Filters were replaced
every 3 or 4 days.
A commercial high-sensitivity PTR-MS (Ionicon Analytik, Innsbruck, Austria),
located in the aforementioned container, was used for the detection of a
broad range of VOCs including isoprene, oxygenated VOCs, acetonitrile and
C6–C7 aromatics with a time resolution of ∼30 s (Table 1). PTR-MS is
an analytical mass spectrometry technique that uses gas-phase hydronium ions
(H3O+) as ion source reagents (Lindinger et al., 1998; Yuan et
al., 2017). Inside the PTR-MS drift tube, VOC species with greater proton
affinity than that of water are soft-ionized by reactions with
H3O+ and then detected by a quadruple mass spectrometer
(Lindinger et al., 1998). This PTR-MS has been validated and utilized in
previous field campaigns (Yuan et al., 2012, 2013; Chen et al., 2014). During
the field measurement, the system was running in multiple-ion mode, where the
quadruple switched between the selected masses. Most of the masses were
recorded for 1 s in every cycle, except for m/z=21 (0.2 s). Background signals
were measured for 30 min every 4 h by diverting the ambient air into a
platinum catalytic converter at 370 ∘C (Shimadzu Inc., Japan).
Aromatics, oxygenated VOCs, isoprene and acetonitrile were calibrated by a
pressurized gas standard (Spectra Gases Inc., USA). Formaldehyde (m/z=31),
formic acid (m/z=47) and acetic acid (m/z=61) were calibrated by
permeation tubes (VICI Inc., USA). Calibrations were conducted before and
after the measurement period, and a single-spot calibration was conducted
every 3 or 4 days with response factors varying within 15 %.
Uncertainties of measured species
were about 5 %–15 %, with the notable exception of formaldehyde,
formic acid and acetic acid. Limits of detection (LODs) for the measured
species were in the level below parts per billion listed in Table 1.
List of reported VOC species along with their protonated m/z, and
5 min limits of detection (LODs).
Protonated
Species
LOD
Protonated
Species
LOD
(m/z)
(ppt)
(m/z)
(ppt)
21
H318O+
69
isoprene
70
39
H318O+ (H2O)
71
MVK+MACR
109
31
formaldehyde
101
73
MEK
198
33
methanol
355
79
benzene
78
42
acetonitrile
87
93
toluene
93
45
acetaldehyde
112
105
styrene
55
47
formic acid
277
59
acetone
77
61
acetic acid
243
MVK: methyl vinyl ketone; MACR: methacrolein; MEK: methyl ethyl
ketone.
Formaldehyde detection is found to be significantly influenced by RH
(Vlasenko et al., 2010; Warneke et al., 2011; Baasandorj et al., 2015).
Calibrations were conducted within a range of RH (0–30 mmol mol-1) to
fit the response curve, which was then applied in ambient measurement
calculations, and this procedure resulted in a measurement uncertainty within
±20 %. Measurements of formic acid by PTR-MS can potentially suffer
interference from ethanol and dimethyl ether when they are present in
significantly higher abundance than formic acid (Baasandorj et al., 2015). At
the background urban site, however, the atmospheric abundance of ethanol and
dimethyl ether in similar urban sites has previously been found to be low
(Good et al., 1998; Monod et al., 2003; Jia et al., 2012), giving rise to a
measurement uncertainty within ±30 %. Influences from ethyl acetate
on acetic acid have been found in field campaigns (Fortner et al., 2009;
Baasandorj et al., 2015; Derstroff et al., 2017). Therefore, during
calculations of acetic acid concentration the m/z=89 (attributed to ethyl
acetate) was introduced to correct for the influences (Yuan et al., 2013).
However, this introduced a measurement uncertainty up to
> 40 %.
In addition to measurements of VOC species by the PTR-MS, several common air
pollutants were also monitored by Thermo Scientific analyzers: O3
(Model 49i, UV photometric O3 analyzer), CO (Model 48i,
trace-level-enhanced gas filter correlation CO analyzer),
NOx (Model 42i, trace level chemiluminescence
NO-NO2-NOx analyzer) and SO2 (Model
43i, trace-level-enhanced pulsed fluorescence SO2 analyzer).
These analyzers were calibrated every 3 days and uncertainties
of these measured air pollutants
were less than 5 %.
Uptake coefficient and deposition velocity
The uptake coefficients (γ) of measured VOC species under ambient
conditions were determined using a Cooney–Kim–Davis (CKD) method (CKD-B in
Li et al., 2016). This CKD-B method is based on the commonly used CKD
solution for correction of the radial diffusion effect (Murphy and Fahey,
1987) and has been shown to have a much better accuracy than the CKD
interpolation method, as CKD-B directly solves a governing differential
equation with numerical methods. The CKD-B can establish the relation between
the sample tube penetration (i.e., Cs/Cr) and γ
of the measured VOC species, which is shown in Fig. 2 derived at an average
ambient temperature of 25 ∘C as an example. For details of the
CKD-B method, see our previous study (Li et al., 2016). Note that the
uncertainty of the determined γ depends on the uncertainty in
Cs/Cr as well as the relation between
Cs/Cr and γ (as in Fig. 2), here with the
derived γ range of 10-7–10-6 (see Sects. 3.3 and 3.4); the
estimated uncertainty of γ
for each VOC species was within 1 order of magnitude. The Reynolds number
(Re) in our experiment was ∼10, which ensured laminar flow
conditions requiring Re < ∼2000 (Murphy and Fahey,
1987; Knopf et al., 2015; Li et al., 2018). The pretube/entrance region
length was 10 cm, and full development of laminar flow was achieved within
the first ∼1 cm for our setup. When a geometric coating thickness
δg is larger than a critical height δc, the
coating surface roughness may potentially distort the well-developed laminar
flow and introduce uncertainties in the calculated uptake coefficients
corrected for molecular diffusion effects using conventional diffusion
correction methods (Li et al., 2018). According to this δc
criterion, the geometric coating thickness of our soil sample
(∼500 µm) was much smaller than the calculated
δc (∼2400 µm) based on our experimental
configuration, ensuring that the soil coating surface roughness effect was
negligible. The uptake coefficients reported here are based on the geometric
surface area of the soil sample, considering that in atmospheric models soil
microstructure is likewise not taken into account (Donaldson et al., 2014a).
The specific surface area of the soil, however, was also measured using a
water vapor adsorption method based on the Brunauer–Emmett–Teller (BET)
adsorption theory (Brunauer et al., 1938) and found to be 15±1.5 m2 g-1. To calculate the BET
surface area, the mass of the adsorbed water in the soil sample after
equilibrium with predefined RH levels was determined by a nondispersive
infrared (NDIR) gas analyzer (type: Li-6262, LI-COR Biosciences Inc.)
operated in differential mode. This BET surface area is comparable to that in
other reports on similar soil types, e.g., 12–15 m2 g-1 (Kahle
et al., 2002) and 8–19 m2 g-1 (Punrattanasin and Sariem, 2015).
Accounting for the BET results, the specific surface area would reduce
γ by a factor of 104 in our case.
Schematic of the uptake coefficients versus the
penetrations of measured VOC species. Derivation of the uptake coefficients
are based on the experimental parameters: volumetric flow rate
F=0.1 L min-1 at 1 atm and 298 K; coated-wall flow tube dimension, d=1.6 cm, L=10 cm.
The primary controlling factors of VOC exchange at the soil–atmosphere
interface include gas transport and the concentration gradient between the
soil surface and the atmosphere. As depicted in Fig. 3, the transport of a
gas species to soil surfaces is governed by three resistances in series: the
aerodynamic resistance Ra, the quasi-laminar layer resistance Rb
and the soil surface resistance Rc (Seinfeld and Pandis, 2016). The
deposition or transfer velocity Vd is the inverse of the sum of
these three resistances (Seinfeld and Pandis, 2016). With the coated-wall
flow tube technique employed in this study, the derived γ reflects the
reaction kinetics on soil and thus
relates to Rc rather than Ra and Rb. Based on the calculated
γ, Rc can be further derived according to the equation Rc=4/(ω×γ) (Donaldson et al., 2014b; Dentener et al., 1996),
where ω denotes the mean molecular speed of the VOC species.
Approximations of Ra and Rb can be achieved using the methodology
developed by Seinfeld and Pandis (2016), i.e., Ra and Rb can be
derived based on Eqs. (1) and (2), respectively.
Ra=1κu∗lnzz0,Rb=5Sc2/3u∗,
where κ is the von Karman constant, u∗ is the friction
velocity, z is the height above the ground, z0 is the roughness length
and Sc is the dimensionless Schmidt number.
Schematic of the resistance model for VOC species dry deposition
on soil. Ra: aerodynamic
resistance; Rb: quasi-laminar layer resistance; Rc: soil surface
resistance.
For the basic assumptions and utilized parameters during derivations of
Ra and Rb, see Sect. 3.2. Finally, Vd can be estimated
as Vd=1/(Ra+Rb+Rc).
Results and discussion
Site-specific characteristics of selected air quality indicators
Figure 4 shows the time series of site-specific ambient air pollutant mixing
ratios observed during the whole measurement period (Fig. 4a) and respective mean
diel courses (Fig. 4b). The range of mixing ratios of selected air quality
indicators like ozone (O3), carbon monoxide (CO), nitrogen oxide
(NO), nitrogen dioxide (NO2) and sulfur dioxide (SO2) are
representative of polluted urban conditions (Bigi and Harrison, 2010).
O3 reveals peak mixing ratios in the afternoon (13:00–17:00 local
time), which corresponds to high sunlight intensities and temperatures at
this time of the day. Coincident with this maximum in O3, reactive
nitrogen species (NO2 and NO) show decreasing trends, which may be
due to decreased local NOx emissions and/or rapid
photochemical oxidation or strong dilution in the boundary layer in the
afternoon. Even though most of the selected air quality indicators reveal a
significant diel cycle, CO, NO and NO2 do not show a typical urban
rush-hour pattern with traffic-associated peaks during morning and late
afternoon. Rather, the site represents an urban background site without
direct influences from strong nearby point sources. The relatively weak diel
course of SO2 mixing ratios with maxima during daytime can also be
assumed to stem from long-range advection or midday entrainment of high-concentration air masses from aloft, instead of the nearby presence of
ground-level emission sources (Bigi and Harrison, 2010).
Time series of observed ambient air mixing ratios of
prominent gas-phase pollutants (a) and respective mean diel courses (b).
In (b), symbols denote individual hourly averaged data, and the thick solid
lines respective mean diel profile. Thin dashed lines represent 1 standard
deviation (±1 SD) from the mean value.
Site-specific characteristics and exchange of VOCs
Figure 5 displays the time series of site-specific ambient air mixing ratios
of VOCs, temperature, relative humidity during the whole measurement period
(Fig. 5a) and respective mean diel courses (Fig. 5b). Among the measured VOC
species, methanol has the highest mixing ratios (Fig. 5a). Methanol is
ubiquitous in the lower atmosphere with mixing ratios in remote regions
reported to be ∼1 ppb (Galbally and Kirstine, 2002; Jordan et al.,
2009). The high mean daytime mixing ratios of 10–20 ppb at this urban
background site suggest a strong impact of anthropogenic emissions on the
local methanol budget. High mixing ratios are also found for its oxidation
products formaldehyde (∼10 ppb) and formic acid (∼5 ppb),
respectively. Formaldehyde is a key reaction intermediate of the atmospheric
oxidation cycle (Li et al., 2016), and hence an indicator of the total amount
of oxygenated VOCs. Its increasing trend during daytime (Fig. 5b) is
indicative of strong photochemical formation. In contrast, formic acid, which
can be formed from ozonization of all terminal double-bonded molecules (Osamu
et al., 1994), shows lower mixing ratios during daytime than during
nighttime, and similar diel trends are also found for other species including
toluene, methanol, acetonitrile and benzene. The daytime decrease
in the latter may be due to
dilution effects by increased daytime boundary layer mixing height and/or
lower atmospheric photochemical formation rates during daytime, even though
some of them (e.g., formic acid) have smaller photolysis and oxidation loss
rates than those of formaldehyde. On the other hand, the most significant
diel profile is observed for isoprene, with mixing ratios peaking in the
midafternoon (around 15:00, local time) followed by a decline in the late
afternoon stabilizing at ∼0.5 ppb during the night. Isoprene can have
an important impact on the atmospheric oxidation capacity due to its high OH
reactivity both in pristine and in polluted urban regions (Williams et al.,
2016). Besides anthropogenic sources like gasoline and diesel traffic exhaust
(Borbon et al., 2001; Wang et al., 2013; Wagner and Kuttler, 2014), the major
summertime source of isoprene can be assumed to be biogenic, i.e., being
emitted from vegetation in a light- and temperature-dependent manner
(Guenther et al., 1993). Thus, during daytime, high mixing ratios of biogenic
isoprene are anticipated at our measurement site, which was surrounded by
different types of vegetation cover (see Sect. 2.2). Following the diel trend
of isoprene, the two primary photochemical oxidation products of isoprene,
methyl vinyl ketone (MVK) and methacrolein (MACR), also exhibit higher mixing
ratios during daytime than during nighttime.
Time series of observed ambient air mixing ratios of VOCs and air
temperature and relative humidity (a), and respective mean diel
courses (b). Colorful lines in (a) denote ambient air
mixing ratios at the outlet of the reference tube Cr, and black
lines represent mixing ratios at the outlet of the sample tube Cs. In (b), symbols denote individual hourly averaged data,
and the thick solid lines respective mean diel profile. Thin dashed lines
represent 1 standard deviation (±1 SD) from the mean value.
Besides primary or secondary surface sources and sinks, the near-ground
nighttime increase (or decrease) of atmospheric trace gas mixing ratios is
favored by the development of a stable and shallow nocturnal boundary
layer (NBL). Any nighttime emission (or deposition) of trace constituents is
confined to the relatively small volume of the NBL where they accumulate (or
get depleted). The growth of the atmospheric boundary layer (ABL) in the
morning hours due to the influx of sensible and latent heat, as well as the
resulting upcoming convection and the respective re-entrainment of air from
the residual boundary layer aloft, being enriched with (or depleted of)
atmospheric trace constituents, may confer a reasonable explanation for any
increased (or reduced) daytime mixing ratios (Kuhn et al., 2002).
The exchange properties of VOCs on
soil can be reflected by comparing Cr (colorful lines in Fig. 5a)
and Cs (black lines in Fig. 5a). The confidence bands (best
estimate ± measurement uncertainties) of Cr and
Cs for each species can be found in Fig. S2 in the Supplement. As
shown in Fig. 5a, during the whole measurement period most of the VOC species
are taken up by the soil, especially for styrene, formaldehyde, toluene and
acetic acid, indicated by the discernable differences between their
Cr and Cs. Only formic acid shows a slightly higher
Cs than Cr, suggesting this compound is likely
emitted by the soil. The time series of the mixing ratio difference
Cr–Cs of measured VOCs are further displayed in
Fig. S3 in the Supplement. The integrated total amount and average surface
flux of each absorbed or emitted VOC species on soil for the whole
measurement period is listed in Table S1 in the Supplement.
Time series and mean diel courses of VOC exchange
Based on the measured Cr and Cs, the uptake
coefficients of examined VOC species can be derived (see Sect. 2.3).
To minimize potential impacts of measurement uncertainties (e.g., random
noise of the instrument) on small Cr–Cs (or large
Cs/Cr) and further on the derived uptake coefficients,
the calculated hourly uptake coefficients (based on the measured
hourly mixing ratio data) were averaged to a daily basis (i.e., daily mean
uptake coefficients). Figure 6a shows the time series of daily mean VOC
uptake coefficients, together with those of ambient temperature and
relative humidity. Eight species (i.e., styrene, toluene, isoprene,
MVK+MACR, acetaldehyde, MEK, acetone and acetonitrile) exhibit a relatively
high initial uptake coefficient, followed by a significant decrease in the
first few days, indicative of progressive saturation of absorption sites on
the pretreated soil sample. For styrene and acetonitrile, this decrease
prevails for the whole 1-month measurement period. Occasionally, some
species show short-term swaps between deposition and emission (see Fig. S4 in
the Supplement for the complete time series of hourly averaged data). This
bidirectional exchange can be caused by fast dynamics in ambient air
conditions like temperature, relative humidity and trace gas mixing ratio,
as well as the respective status of soil saturation. Interestingly, formaldehyde only
rarely shows emission from soil, suggesting a strong capacity of the soil
sample for absorption under ambient conditions. This result to some extent
challenges our previous laboratory-based observation that soil could also act
as a source for formaldehyde, when it had been saturated with formaldehyde
prior to back-flushing with pure N2, i.e., the uptake of
formaldehyde by soil was shown to be reversible (Li et al., 2016). Indeed,
the range of formaldehyde mixing ratios observed in Beijing was rather high
for most of the time, and extremely rapid changes in the mixing ratio to below a
compensation point, as applied in the laboratory study, hardly occurred in
the field. On the other hand, the anticipated high levels of oxidants for
heterogeneous reactions on the soil under field conditions may foster the
chemical conversion/oxidation of formaldehyde, which could prevent its
accumulation, saturation and subsequent release (see below). Given the poor
understanding of formaldehyde's budget (Jacob, 2000; Wagner et al., 2002),
more research is needed to elucidate the exchange behavior of formaldehyde on
various types of soils under ambient conditions. In addition, the variability
of uptake coefficients of some species (e.g., isoprene, MVK+MACR,
acetaldehyde and formic acid) closely follow the trend of ambient relative
humidity and temperature, suggesting that these environmental parameters
influence the exchange of respective VOC species.
Time series of the uptake coefficients of measured VOC
species and air temperature and relative humidity (a), and respective mean
diel courses (b). In (a), each symbol represents daily averaged data and the
yellow shaded areas indicate the days when measurements were not
continuously running all day long. In (b), symbols denote individual hourly
averaged data, and the thick solid lines respective mean diel profiles. Thin
dashed lines represent 1 standard deviation (±1 SD) from mean
values.
Mean diel variations of VOC uptake coefficients as well as those of ambient
relative humidity and temperature are presented in Fig. 6b. In
general, uptake coefficients are quite stable over the whole day.
The observed uptake/emission in Fig. 6 can be caused by pore diffusion and
soil surface processes (i.e., adsorption/desorption equilibrium and chemical
reactions). As aforementioned, the timescale of VOC diffusion through soil
pores is around 25 min. This timescale is several orders less than our whole
field campaign time period (i.e., 1 month), suggesting that pore diffusion is
not the limiting factor of the uptake/emission found here. After the
significant absorption saturation on
soil in the first few days (see Fig. 6a), the subsequent relatively stable
uptake for most of the VOC species could be due to chemical reactions on soil
surfaces. Our previous laboratory study of formaldehyde uptake on soil has
proved that the observed uptake is a combination of adsorption/desorption
equilibrium and chemical reactions (Li et al., 2016). From a perspective of
kinetic gas theory, the derived uptake coefficients can be further used to
determine VOC surface reaction rates on soil which are only caused by reactions on soil surfaces instead
of diffusion into soil pores under steady-state conditions (i.e., after
significant absorption saturation of the soil sample in the first few
measurement days in Fig. 6a). The soil surface reaction rate is described as
(γ×ω)/4×[VOC(g)]. γ and ω
are the daily average uptake coefficients and mean molecular speed (at an
average temperature of 298 K) of each VOC species, respectively. [VOC(g)] is
the VOC mixing ratio in ambient air (i.e., Cr). Accordingly, the
corresponding surface reaction (or wall loss) rate coefficient kw
is (γ×ω)/4, equivalent to the inverse of Rc. Note
that only formic acid shows negative uptake coefficients for most of the
measurement time period, and its emission rate cannot be described by the
above reaction rate expression accounting for surface uptake processes.
Instead, the soil surface emission rate of formic acid is calculated from a
flux point of view, which equates to F×(Cr-Cs)/S. F is the volumetric flow rate in the sample
tube and S is the geometric surface area of the soil sample. The time
series of surface reaction rates are shown in Fig. S5 in the Supplement.
kw is shown in Table S3 in the Supplement and further discussed
in the following section.
Exchange of VOCs interpreted in terms of long-term mean uptake
coefficients and deposition velocities
Figure 7 shows the averaged uptake coefficients for days with continuous
instrumental operation (16 days within the 1-month field measurement) for
each VOC species. The vast majority of VOC species reveal positive uptake
coefficients, indicating that these species tend to be absorbed and retained
or converted into other products in the soil (net soil influx). Highest
uptake coefficients are found for styrene and formaldehyde, with mean values
on the order of 10-6. The uptake coefficient of formaldehyde is in the
same range as reported earlier for laboratory experiments, where sterilized
agricultural soil was flushed by pure N2 containing different
mixing ratio levels of formaldehyde under varying RH conditions (Li et al.,
2016).
Box-and-whisker plots of the uptake coefficients of
measured VOC species, based on daily averaged data. The 25th, 50th and
75th percentiles and minimum and maximum are indicated by bars, and mean values by
squares.
In Fig. 7, only formic acid reveals a negative mean uptake coefficient, which
is indicative of emissions from soil (Li et al., 2018). This short-chain
organic acid is regarded as one of the terminal products in the oxidation
processes of many VOC species present in the atmosphere (Charbouillot et al.,
2012). Therefore, the heterogeneous formation from previously
adsorbed/absorbed VOCs may confer a reasonable explanation for its
accumulation and subsequent release, as is further discussed in the following
sections.
As mentioned previously, the long-term mean uptake coefficients can be used
to derive the soil surface reaction (or wall loss) rate coefficient
kw of each VOC species, which reflects the soil surface exchange
properties. Here kw has a unit of centimeters per second
(cm s-1) and can be interpreted as a deposition velocity without gas
transport resistance (i.e., Ra+Rb) effects (Pöschl et al.,
1998). As the initial soil sterilization procedure eliminates potential
impacts from soil bacteria, the observed exchange of these VOC species is
primarily influenced by physicochemical factors. To have a general
understanding of how different physicochemical factors may affect
kw, the calculated kw values of each VOC species are
listed in Table S3 in the Supplement, together with the basic physicochemical
parameters possibly related to the trace gas exchange (i.e., gas-phase
reaction rate coefficients with OH radicals and O3, Henry's law
constant, vapor pressure and octanol–water partition coefficient). In
general, differences in kw found among these species cannot be
explained by any of the physicochemical factors alone, which suggests that
VOC exchange at the atmosphere–soil interface is a complex multifunctional
process.
Deposition velocity Vd is a key parameter used in models to
describe trace gas uptake by soils and is the inverse of the sum of three
resistances in series: the aerodynamic resistance Ra, the
quasi-laminar layer resistance Rb and the soil surface resistance
Rc (Fig. 3). As described in Sect. 2.4, only Rc can directly be
derived from the calculated uptake coefficients. Ra and Rb
are calculated adopting the approach proposed by Seinfeld and Pandis (2016):
in Table 2, the case of neutral stable temperature profiles is adopted for
Ra calculation (Eq. 19.14 in Seinfeld and Pandis 2016). The
season is set to autumn (cropland before harvest). To assess the impact of
Ra and Rb on derived Vd, three types of land use
categories including shrubs (category 1 in Table 2), urban land (category 2)
and barren land (category 3) are selected mimicking our field environmental
conditions and soil type characteristics. The detailed parameters adopted for
Ra and Rb derivation and the calculated Ra,
Rb, Rc and Vd are shown in Table 2. As Rc≫Ra+Rb, the VOC uptake is not limited by atmospheric gas-phase
transport (Ra+Rb) or by land use type. Rather the uptake on
the soil surface (Rc) is the primary rate-limiting step for dry
deposition of these VOC species, even for the largest γ observed in
our study. Note that Vd of formic acid intrinsically reveals
negative values, as this organic acid is released from the soil.
Parameters used for resistance calculations to infer the relative
importance of Rc versus Ra and Rb, and the resulting
deposition velocities (Vd) of measured VOC
species.
VOC species
γ
ω
D
u* (cm s-1)
z0 (cm)
Rc
Ra (s cm-1)
Rb (s cm-1)
Vd (cm s-1)
(×10-7)
(cm s-1)
(cm2 s-1)
1
2
3
1
2
3
(s cm-1)
1
2
3
1
2
3
1
2
3
Styrene
12.30
24 636
0.08
30
45
20
10
100
4
132
0.67
0.32
1.12
0.27
0.18
0.40
0.008
0.008
0.007
Formaldehyde
8.92
45 870
0.17
30
45
20
10
100
4
98
0.67
0.32
1.12
0.15
0.10
0.23
0.01
0.01
0.01
Toluene
6.74
26 194
0.08
30
45
20
10
100
4
227
0.67
0.32
1.12
0.26
0.17
0.38
0.004
0.004
0.004
Isoprene
6.06
30 468
0.09
30
45
20
10
100
4
217
0.67
0.32
1.12
0.24
0.16
0.36
0.005
0.005
0.005
Acetic acid
5.77
32 435
0.12
30
45
20
10
100
4
214
0.67
0.32
1.12
0.20
0.13
0.30
0.005
0.005
0.005
MVK+MACR
4.80
30 029
0.10
30
45
20
10
100
4
278
0.67
0.32
1.12
0.23
0.15
0.35
0.004
0.004
0.004
Acetaldehyde
3.63
37 876
0.13
30
45
20
10
100
4
291
0.67
0.32
1.12
0.19
0.12
0.28
0.003
0.003
0.003
Methanol
3.43
44 414
0.16
30
45
20
10
100
4
263
0.67
0.32
1.12
0.16
0.11
0.24
0.004
0.004
0.004
MEK
2.27
29 609
0.09
30
45
20
10
100
4
595
0.67
0.32
1.12
0.23
0.16
0.35
0.002
0.002
0.002
Acetone
2.16
32 990
0.11
30
45
20
10
100
4
561
0.67
0.32
1.12
0.21
0.14
0.32
0.002
0.002
0.002
Acetonitrile
2.12
39 237
0.16
30
45
20
10
100
4
480
0.67
0.32
1.12
0.17
0.11
0.25
0.002
0.002
0.002
Benzene
1.89
28 448
0.09
30
45
20
10
100
4
745
0.67
0.32
1.12
0.24
0.16
0.36
0.001
0.001
0.001
Formic acid
-2.15
37 044
0.15
30
45
20
10
100
4
-502
0.67
0.32
1.12
0.17
0.12
0.26
-0.002
-0.002
-0.002
γ: uptake coefficient; ω: mean molecular speed at
25 ∘C; D: molecular diffusion coefficient at
25 ∘C; u*: friction velocity, the listed values are
averaged between the day and night cases by Zhang et al. (2003); z0:
aerodynamic surface roughness length, the listed values are referred to Zhang
et al. (2002); Rc: soil surface resistance; Ra: aerodynamic
resistance, calculated using the equation (19.14) in Seinfeld and
Pandis (2016), where the reference height z is set to 300 m; Rb:
quasi-laminar layer resistance, calculated using the Eq. (19.17)
in
Seinfeld and Pandis (2016), where the air kinematic viscosity ν is
0.16 cm2 s-1; Vd: deposition velocity. The numbers
in the table header denote different land use categories adopted from Zhang
et al. (2002, 2003): 1: shrubs; 2: urban; 3: barren land (mostly desert).
Previous VOC exchange studies on various soil types such as agricultural
soil, tropical soil, plantation floor and forest understory, etc., have
spanned a huge range of Vd with 3 orders of magnitude
(0.01–1 cm s-1) for the VOC species investigated here (Hartmann et
al., 1991; Karl et al., 2005; Sanhueza et al., 2004; Schade and Custer, 2004;
Stickler et al., 2007; Jordan et al., 2009; Schade et al., 2011; Gordon et
al., 2014b; Cleveland and Yavitt, 1997). Our calculated Vd
(0.001–0.01 cm s-1) is at the very low end of previous studies. This
could be due to a variety of reasons:
Our soil sample is bare soil without any vegetation cover while previous
flux studies included different types of vegetation covers (grass, leaf
litter, agricultural crops, etc.), which might significantly alter the
measured deposition velocity.
Our soil sample is sterilized in order to
investigate the physicochemical processes on soil, yet the soil bacteria can significantly modify the VOC
exchange, as can be expected based on the previous studies. In fact, several studies have demonstrated that soil
bacteria can consume atmospheric VOCs (Misra et al., 1996; Cleveland and
Yavitt, 1998; Stacheter et al., 2013; Lynch et al., 2014).
From the physicochemical point of view, low Vd may also arise
from competition among different VOC species for surface absorption sites, as
has been observed in controlled laboratory studies by Lichtin et al. (1996)
for photocatalytic reactions of binary VOC mixtures on TiO2
surfaces. Likewise, interfering effects of O3, OH and NO3
radicals on VOC photocatalytic TiO2 surface reactions were
demonstrated (Ao et al., 2004). We assume that this phenomenon is universal
for catalytic surfaces and also applies for soil.
To further validate the plausibility of our calculated γ and derived
Vd, we calculate the surface resistance, Rc, using a
regional-scale numerical model developed by Wesely (Seinfeld and Pandis,
2016; Wesely, 1989), which considered only physicochemical factors affecting
gas deposition on ground surface for formaldehyde, acetic acid and
acetaldehyde as typical VOC representatives. As a proxy for bare soil
properties in the present study, the land use type is set to barren land
(mostly desert), and the seasonal category is chosen as autumn (cropland
before harvest). All other input parameters are the same as used in the
original literature (Wesely, 1989). The model outputs a Rc for
formaldehyde of 167 s cm-1, which is in fair agreement with our
results (98 s cm-1). Due to a very small effective Henry's law
constant adopted in the model (15 M atm-1 for water with near-neutral
pH) the derived Rc for acetaldehyde is much higher than that based on
our measurements (66 667 vs. 291 s cm-1), corroborating our
relatively low range of observed VOC uptake. In contrast, acetic acid bears a
much higher effective Henry's law constant (4×106 M atm-1), revealing a much smaller Rc than that based on our
measurements (0.3 vs. 214 s cm-1), underpinning the intense impact of
VOC physicochemical characteristics on modeled uptake resistances.
VOC exchange dependence on environmental parameters
In order to explore potential effects of environmental factors on the
exchange of these VOC species at the atmosphere–soil interface, the relation
between uptake coefficients and ambient relative humidity, temperature and
mixing ratio (C) is further examined, and those VOC species showing
relatively significant dependencies are shown in Fig. 8. To interpret the
uptake coefficient dependence on a single parameter, the others should remain
constant. Under ambient conditions, however, all the environmental parameters
change simultaneously and some of them are even closely related (e.g.,
between RH and T; see Fig. 5). Therefore in Fig. 8 we present the
RH/T dependence as the C varies within a narrow range (i.e.,
this range can be considered constant when compared with the whole variation
scope of C during the entire measurement time period). The C range for
the species in Fig. 8 is 0.5–0.6 for isoprene, 0.8–1.0 for MVK+MACR,
2.0–6.0 for formic acid, 8.0–12.0 for formaldehyde and 1.5–2.5 for
acetaldehyde. These ranges are determined following the criterion of A±B, where A means the 1-month average of the ambient mixing ratios of each
species and B is determined by using two criteria.
It should be as small as possible.
The selected range can provide a
data set large enough for plotting the RH/T dependence box chart. Regarding
the C dependence in Fig. 8, the data are only adopted when RH equals
50 %.
Dependence of uptake coefficients on ambient relative
humidity (RH), temperature (T) and mixing ratios (C). The 25th, 50th and
75th percentiles and minimum and maximum of the box-and-whisker plots are indicated by
bars. The uptake coefficient dependence is based on the hourly averaged data,
and the RH and T dependences are plotted when C is varied within a very
narrow range (nearly constant) and C dependence is plotted when RH equals
50 %. Note that negative uptake coefficients indicate emission. For
details see text.
RH affects the amount of surface-adsorbed water and can accelerate or slow
down trace gas uptake rates (Crowley et al., 2010). High-RH-induced condensed
water may attract water-soluble or hydrophilic gas species and hence enhance
their uptake (Pei and Zhang, 2011), or decrease their net emission. This
mechanism applies, for example, to hydrophilic formaldehyde and formic acid (see
Table S3 for respective Henry's law constants). On the other hand, more
water molecules on soil surfaces tend to repel the hydrophobic species more
strongly or reduce gas uptake by means of competitive adsorption effects
between water molecules and gas species (Ruiz et al., 1998; Goss et al.,
2004; Donaldson et al., 2014a; Li et al., 2016). However, the uptake
coefficients of hydrophobic isoprene and its primary degradation products
(i.e., MVK+MACR) also increase at high RH. This counterintuitive dependence
may also be explained in another way: more water molecules can push more
hydrophobic species into the soil bulk, leaving additional adsorption sites
on soil surfaces and thereby increasing its uptake; as the soil becomes dry,
the VOC molecules in the soil bulk will remain in situ considering that the
timescales of soil bulk diffusion are considerably longer than on soil
surfaces. From the physical perspective of vapor pressure, increased
temperature leads to decreased trace gas uptake and increased emission. This
is in line with the decreased uptake of isoprene at higher temperatures shown
in Fig. 8. However, the uptake coefficients of acetaldehyde show a slight
increasing trend as a function of T.
Even though the calculation of uptake coefficients intrinsically accounts for
the gas-phase mixing ratios, higher mixing ratios have been shown to reduce
uptake coefficients (Sassine et al., 2010; Wang et al., 2012). A negative
effect of increased mixing ratios on uptake coefficients is also observed for
isoprene and acetaldehyde in Fig. 8. The negative effect of mixing ratios on
uptake coefficients can be understood as competition among the individual VOC
molecules for reactive uptake sites, or with other VOCs whose mixing ratios
show a simultaneous increase (Li et al., 2016). Our previous laboratory
experiments on formaldehyde (Li et al., 2016) showed that this trend was more
pronounced under dry conditions (RH = 0 %) than under humid
conditions (RH = 40 %), in agreement with the formaldehyde pattern
shown here.
VOC exchange correlation analysis
As discussed above, the uptake dynamics of one individual VOC species may be
biased, either (i) by competitive co-absorption of other VOCs or trace gases
from ambient air (Lichtin et al., 1996; Ao et al., 2004), (ii) by
formation on the soil through heterogeneous conversion of precursor compounds
that have been absorbed earlier (Ammann and Pöschl, 2007; Pöschl et
al., 2007), or (iii) by depletion of the individual VOC species due to
heterogeneous degradation. To explore potential interactions/interference of
VOC species among each other, correlation analyses of the exchange rates
(i.e., the concentration difference between the reference channel and the
sample channel Cr–Cs times the volumetric flow rate
F) of measured VOC species are conducted for each pair of species. The
results are presented in Fig. 9 in terms of Pearson correlation coefficients,
together with the molecular structure of each investigated species. The
interplay of sorption, heterogeneous reactions and desorption kinetics of
VOCs is complex, and heterogeneous reactions may require time periods from
milliseconds to weeks or even months to reach equilibrium (Xing and
Pignatello, 1996; Ammann and Pöschl, 2007). Hence, to also account for
slow kinetics, the correlation analysis in Fig. 9 is based on daily
integrals. VOC exchange rates instead of uptake coefficients are used to
allow for a budget approach. Positive correlations are indicated in red
colors, and some pairs of VOC species show high positive correlation (deep
red color code in Fig. 9), suggesting they have similar exchange
characteristics. For example, MVK and MACR are the first-generation oxidation
products of isoprene (Jordan et al., 2009). Thus, the observed high
correlation coefficient between MVK+MACR and isoprene can be explained by
their similar molecular structures, shown in Fig. 9. The same holds for the
strong correlation between methanol and formaldehyde, between methanol and acetone,
and for MEK and acetone: similar molecular structures and functional
groups result in analogous exchange and reaction mechanisms on soil.
Correlation of the exchange of measured VOC species
(upper left) and their molecular structures (lower right). Correlation
between each pair of VOCs is reflected by the correlation coefficient, shown
in the plot. The correlation coefficient between each individual species
itself is 1, a correlation coefficient of 0 means no correlation, and -1
implies complete anti-correlation.
Negative correlations in Fig. 9 are indicated in blue colors. As
aforementioned, formic acid is at the very end of the VOC oxidation chain
and is exclusively emitted from the soil sample while all other VOCs tend to
be taken up. Thus, correlations of formic acid with other VOCs are negative
as such (blue in Fig. 9). High negative correlation coefficients are obtained
between formic acid and some species (i.e., acetone, isoprene, formaldehyde,
styrene and methanol), indicative of possible generation and emission of
formic acid due to heterogeneous transformation of these deposited compounds.
Implications for atmospheric chemistry
Formic acid formation through heterogeneous transformation of
deposited VOCs
We know from the above discussions that several VOC species including
acetone, isoprene, formaldehyde, styrene and methanol show high
anti-correlation with formic acid, suggesting the existence of one or
several pathways for formic acid formation through heterogeneous reactions
of these VOC precursors.
In the atmosphere, photo-oxidation of acetone contributes to the abundance of
formic acid, and the dominant pathway for formic acid formation via acetone
photo-oxidation is the reaction of OH radicals with acetone-derived
formaldehyde (Chattopadhyay et al., 2015). Formic acid production through
photo-oxidation of isoprene has been found under high NOx
circumstances (Paulot et al., 2009). Under ambient conditions, gas-phase
reactions of styrene with both OH radicals and O3 can occur,
with formaldehyde and benzaldehyde as major products and formic acid as the
minor (Tuazon et al., 1993). Methanol has been reported to play an important
role in upper tropospheric photo-oxidation chemistry via its contribution to
the HOx budget after its oxidation to formaldehyde (Tie et
al., 2003; Singh et al., 1995, 2000, 2004; Colomb et al., 2006). Notably,
formaldehyde is an important intermediate of VOC oxidation and a direct
precursor of formic acid (Adewuyi et al., 1984; Chameides, 1984). Moreover,
the results in Sect. 3.2 and 3.3 tell us that formaldehyde shows continuous
and even increasing uptake during the whole field measurement (see Figs. 5a
and 6a). All these results suggest formaldehyde may act as the best candidate
for heterogeneous formation of formic acid on soil.
In terms of physicochemistry, formaldehyde is much less stable than formic
acid (∼1 day versus ∼25 days of mean atmospheric chemical lifetime;
see Millet et al., 2015), indicating its faster turnover rates on soil
surfaces. Moreover, the mean retention coefficient of formaldehyde has been
shown to be considerably higher than for formic acid in cloud/ice water (Jost
et al., 2017), inferring a reasonable explanation for the preferential
release of the organic acid from the soil. Furthermore, aldehydes in general
undergo accretion reactions (i.e., aldol condensation-type reactions) in
acidic media and similar chemistry has been shown to occur on mineral oxides
(Li et al., 2001); therefore mineral-rich bare soils can serve as a sink for
these compounds. According to our results, formaldehyde is a relatively
reactive short-term intermediate for formic acid production, rather than
being directly released to the atmosphere under authentic ambient air
oxidizing conditions in Beijing city. In general, a catalytic effect of soil
can be anticipated by its composition of a variety of mineral oxides
(silicon oxide, iron oxide and titanium oxide, etc.). Therefore, our soil
sample may serve as a catalytic surface for degradation of the deposited
precursors with formaldehyde as the most important intermediate, which can be
further oxidized to build up formic acid by heterogeneous reactions on the
soil, followed by formic acid emission. This catalytic effect may be further
enhanced by the co-existence of other deposited oxidants (O3, OH
radical, NO2 and peroxides, etc.) on the soil surfaces. More
research is needed to confirm the speculation made here.
Physicochemical reactions on bare soil and soil-derived dust may
act as a potential source of formic acid
The only VOCs that have been observed to be released from the soil sample
investigated here is formic aid, which represents a final organic product of
the VOC oxidation cascade. Formic acid is one of the most abundant organic
acids in the atmosphere, existing in the gas phase, cloud and rain water as well
as snow and even polar ice (Chebbi and Carlier, 1996; Sanhueza and Andreae,
1991; Maupetit and Delmas, 1994; Sempére and Kawamura, 1994; Löflund
et al., 2002; van Pinxteren et al., 2005; Mungall et al., 2018). In remote
regions like the Amazon forest, short-chain organic acids have been shown to
be responsible for 60 %–80 % of rainwater acidity (Galloway et al., 1982;
Stavrakou et al., 2012), and also over boreal forests and in urban areas they
contribute significantly to the free acidity in precipitation (Khare et al.,
1999; Stavrakou et al., 2012) and hence can regulate pH dependence of
aqueous reactions in clouds (Vet et al., 2014) and can contribute to
acidification of soil.
Gas-phase photochemical oxidation of biogenic VOCs is considered to be the
dominant global atmospheric source of formic acid. Modeled budget analyses
implicate the existence of one or more large missing sources for formic acid,
i.e., the annually produced formic acid (100–120 Tg yr-1) is 2 to 3 times higher than can be explained based on the current understanding of
primary and secondary (gas-phase) atmospheric processes and aqueous-phase
cloud/rain chemistry (Barth et al., 2007; Paulot et al., 2011; Veres et al., 2011;
Le Breton et al., 2012; Stavrakou et al., 2012; Cady-Pereira et al., 2014;
Schobesberger et al., 2016; Millet et al., 2015). This is the case even when
using a master chemical mechanism (MCM) that was updated with recently
proposed additional photochemical formation pathways for formic acid, like OH
oxidation of isoprene and aromatics (Yuan et al., 2015). This suggests the
existence of either a key gap in current understanding of hydrocarbon
oxidation or large and widespread, yet unidentified sources for formic acid
(Millet et al., 2015).
Previous model estimations of soil emissions of formic acid were based on a
few available field measurements (Paulot et al., 2011; Millet et al., 2015).
These ambient studies found formic acid emissions from dry savanna soil
(Sanhueza and Andreae, 1991) and coniferous forest soil (Enders et al.,
1992), respectively, to be an important source of the local formic acid
budget. The former study reported a daily average emission rate of 1.4×10-1 nmol m-2 s-1, which is much larger than the
estimated long-term mean emission rate of 6×10-3 nmol m-2 s-1 (see Table S2 in the Supplement) in the
present study. This large discrepancy could be due to different
emission/formation mechanisms of formic acid. For the dry savanna soil,
emissions of formic acid may be caused by soil bacteria or physicochemical
partitioning between the soil reservoir and the atmosphere. In our case,
emissions are rather attributed to physicochemical processes on soil (more
specifically, heterogeneous oxidation processes) instead of microbial
activities and reservoir of the soil itself, due to the applied sterilization
and flushing procedures on the soil sample prior to the field experiment. To
the best of our knowledge, this study is the first trial to evaluate the
potential contribution of physicochemical processes on soil under real ambient conditions to the atmospheric
budget of formic acid. Assuming the heterogeneous formation of formic acid
also applies to other bare soil types around the globe, a global formic acid
source strength of ∼0.24 Tg yr-1 can be estimated using the
average emission rate obtained here and a global barren land (i.e., bare soil
and land with very sparse vegetation) surface area of ∼2.8×107 km2 (Roser and Ritchie, 2018). This source strength due to
heterogeneous reactions on bare soils is comparable to that from
anthropogenic and biofuel emissions (0.4 Tg yr-1 by Millet et al.,
2015) but still much less than the missing source strength. Note that the
magnitude of the emission rate here used for calculation also depends on the
mixing ratio levels of ambient VOC precursors and other environmental
parameters such as temperature, relative humidity and photochemistry on soil
surfaces. Due to the design of our experimental setup, no sunlight reaches
the soil surfaces (see Sect. 2.2). But one can imagine that the existence of
sunlight would enhance the catalytic effect of soil minerals (e.g., titanium
oxide), and the soil surface will become hotter and thus make soil dry out
faster. These changes may influence the exchange rates of the examined VOCs
in the following ways:
High catalytic efficiencies may accelerate transformations of deposited
VOC precursors and the formation/emission of formic acid.
High temperatures
of soil may let more adsorbed VOC molecules escape from soil surfaces through
evaporation and decrease their uptake.
Low amounts of water in soil may
increase the uptake of some hydrophobic VOC species and decrease the uptake
of some hydrophilic VOCs.
The combined effect of these three aspects may even tell another different
story, which deserves further studies. In a real soil situation, the
physicochemical (i.e., abiotic) processes are often combined with biotic
processes. The dominance of one over the other is influenced/controlled by
changing environmental factors (i.e., temperature, relative humidity and
photochemistry) and/or soil types. However, here we assume that
physicochemical processes on soil surfaces (more likely on the soil solid
phase through heterogeneous chemistry) can be a common phenomenon, which is
occurring in parallel with biotic processes. This is because the solid phase
of soil, which includes minerals and organic matter (with minerals' content
much higher than organic matter), is generally stable in nature
(https://www.ctahr.hawaii.edu/mauisoil/a_comp.aspx, last access: 25
June 2018). We think the results obtained in our study can provide a helpful
reference regarding the potential contribution of soil particles to formic
acid budget from a physicochemical (heterogeneous chemistry) point of view,
especially when the soil is dry and the microbial activities are low under
some specific situations. Considering the still poorly understood budget of
formic acid (Millet, 2012; Paulot et al., 2011), more investigations are
needed to quantify the contributions of different types of soil as a
potential source of formic acid under different environmental conditions.
Wind erosion is an important process in generating mineral dust aerosols
(Zender et
al., 2011). Thus, our soil-based formic acid formation mechanism may also
apply to soil-derived dust. Indeed, field measurements have identified formic
acid to be among the most abundant carboxylic acids in collected mineral dust
(Falkovich et al., 2004; Khare et al., 1998). However, dust was treated as a
sink of gaseous formic acid in recent model simulations (with a simulated
dust uptake of 1.2 Tg yr-1 in Millet et al., 2015; Paulot et al.,
2011) based on laboratory-observed uptake of formic acid on clay minerals
followed by fast surface saturation (Hatch et al., 2007). Here, we may
predict heterogeneous transformations of other co-adsorbed VOCs in the
ambient air (e.g., formaldehyde) followed by emission of formic acid on dust,
preferentially under low relative humidity conditions (Fig. 8). Based on our
observed emission rate, a global emission strength can be roughly estimated
by assuming that dust particles have a mean diameter of 2 µm and a
density of 2.2 g cm-3 as adopted by Hatch et al. (2007). Using an
average atmospheric dust loading of 18 Tg (Kok et al., 2017) would result in
a formic acid source of ∼2.4×10-5 Tg yr-1. Note that
estimating the emission of dust aerosol particles, a emission rate for formic
acid that is 10 000 times lower should be applied to account for the real
available surface (versus the geometric surface used here for soil, to
reflect common model input needs). Clearly, this additional formic acid
source on dust is much smaller and can be considered negligible. However, our
observed formic acid emission to some extent challenges model applications of
high initial uptake coefficients on clay minerals derived from laboratory
experiments, and previous model simulation may need to be re-constrained.
Aging of organic aerosols by heterogeneous reactions with OH radicals has
been proposed as an important secondary source of formic acid (Molina et al.,
2004; Paulot et al., 2011), and formic acid heterogeneous production was
indeed observed during organic aerosol aging in the laboratory (Eliason et
al., 2003; Molina et al., 2004; Walser et al., 2007; Vlasenko et al., 2008;
Malecha and Nizkorodov, 2016). Stavrakou et al. (2012) modeled the
heterogeneous oxidation of organic aerosols as a source of formic acid
assuming that one molecule of formic acid is formed per molecule of OH lost.
They calculated an extra global annual formic acid flux of 27 Tg, which is
still less than the missing source invoked to explain their remote sensing
total column observations (see also Millet et al., 2015). However, based on
high concentrations of reactive oxygen species prevailing in
atmospheric aerosol particles (Chung et al., 2006; Verma et al., 2015; Tong
et al., 2016), we may consider more VOC precursors being oxidized to formic
acid than has been adopted in the model.
Conclusions
VOC heterogeneous chemistry at the gas–surface interface of soils play a
central role in regulating atmospheric trace gas mixing ratios. In the
present study, a coated-wall flow tube system coupled with a PTR-MS analysis
was adopted to investigate the exchange of common VOC species at the
atmosphere–soil interface at real-world ambient air conditions of an urban
background site in Beijing. Almost all VOCs show an average net deposition on
the pretreated sterilized soil, examined over an extended exposure of one
month. The derived deposition velocities are found to be at the lower end of
ranges reported for natural soil habitats, but were in fair agreement with
models based on pure physicochemistry. Only formic acid displays a long-term
emission. The net emission of formic acid is solely due to physicochemical
processes (i.e., heterogeneous transformations of absorbed VOC precursors)
on soil, which represents an
additional ground-based source of this organic acid.
At ambient atmospheric conditions, both the relatively low uptake
coefficients derived for the majority of VOC species and the emission of
formic acid from the soil to some extent challenge the applicability of
models using uptake coefficients derived from laboratory-based uptake
measurements, where single VOC species or simple mixtures are supplied using
purging air devoid of oxidizing agents. Field measurements as presented
here, with all relevant parameters changing in concert, may call attention
to the existence of yet unknown interference or synergetic effects.
As our soil sample is sterilized, the uptake and emission characteristics
observed in this study can reflect the contribution of abiotic processes on
soil regarding VOC exchange at the atmosphere–soil interface. However,
natural soils are a complex ecosystem including leaf litter, plant roots,
microorganisms and soil particles. Taking the biotic processes and different
soil types into account may produce different results from what we observed here.
Previous studies have shown that soil can be a source of short-chain
oxygenated VOCs and terpenes due to emissions of soil vegetation (e.g., grass
and crops), degradation of leaf litter and other activities of soil living
organisms (Schade and Goldstein, 2001; Hayward et al., 2001; Gray et al.,
2010; Chen et al., 2004; Lin et al., 2007; Scholler et al., 2002; Rossabi et
al., 2018). For example, Leff and Fierer (2008) found that litter samples
could produce more types of VOCs than the soil samples without litter covers,
indicating degradation of soil litter can be an important source of VOC
emission. On the other hand, other studies have observed deposition of
several categories of VOCs (e.g., alcohols, aldehydes and monoterpenes) on
various types of soils (Asensio et al., 2007a, 2008; Aaltonen et al., 2013;
Gray et al., 2014). Considering that the results obtained in the present
study can only address the effects of physicochemical processes on VOC
exchange, follow-up studies are needed to explore the contribution of soil
living organisms (e.g., bacteria, fungi) to VOC exchange at the
soil–atmosphere interface.