Introduction
Dinitrogen pentoxide (N2O5) is an efficient nocturnal sink for
nitrogen oxides (NOx; Dentener and Crutzen, 1993; Brown et al.,
2006). N2O5 exists in a rapid temperature-dependent thermal
equilibrium with the nitrate radical (NO3) – one of the most important
oxidants at nighttime (Wayne et al., 1991).
Although NO3 and N2O5 levels can be suppressed by the rapid
titration of NO3 against NO and volatile organic compounds (VOCs) in
urban areas (Brown et al., 2003b), heterogeneous uptake by
aerosol particles, fog, and cloud droplets is often found to be the major
pathway for direct N2O5 removal (Bertram and Thornton,
2009; Wagner et al., 2013; Brown et al., 2006; Chang et al., 2011; Thornton et
al., 2003). N2O5 can produce nitryl chloride (ClNO2) on
chloride-containing aerosols, which serves as an important reservoir of
NOx (Finlayson-Pitts et al., 1989; Thornton et al., 2010; Phillips et
al., 2012). It has been found that levels of particulate nitrate formed
through the hydrolysis of N2O5 at nighttime were comparable to those
produced from the reaction of NO2 with the OH radical during daytime
(Geyer et al., 2001). Furthermore, ClNO2 can be
photolyzed into NO2 and atomic chlorine (Cl) after sunrise, resulting
in significant impacts on daytime photochemistry, for example trace gas
degradation and ozone formation (Osthoff et al., 2008; Sarwar et al.,
2014; Riedel et al., 2012; Mielke et al., 2013). Thus, it is of great
importance to understand N2O5 and ClNO2 chemistry in the
nocturnal boundary layer of various environments.
The heterogeneous reaction of N2O5 and activation of
ClNO2 are parameterized by the N2O5 uptake coefficient
(γN2O5) and ClNO2 product yield (ø), which are defined as the reaction probability of
N2O5 upon its collision on an aerosol surface and the number of
ClNO2 molecules formed per lost N2O5 molecule upon uptake, respectively (Wagner et al., 2013; Brown,
2006; Roberts et al., 2009). Previous laboratory studies have shown a large
variability of γN2O5 (0.0002–0.3) depending
on the physical characteristics of the substrates (e.g., aerosol surfaces,
water droplets, and ice and crystal surfaces), environmental conditions (e.g.,
acidity, relative humidity, and temperature), and chemical composition of
aerosol particles (e.g., nitrate, sulfate, black carbon, and organic coating; Sander et al., 2006; Chang et al., 2011; Anttila et al., 2006; Cosman et
al., 2008; Thornton and Abbatt, 2005; McNeill et al., 2006). To reveal the
effects of each factor on N2O5/ClNO2 chemistry, several
parameterizations of γN2O5 and ø have been
proposed during the last decade (Riemer et al., 2003; Evans and Jacob,
2005; Anttila et al., 2006; Davis et al., 2008; Riemer et al., 2009; Griffiths
et al., 2009). For example, Bertram and Thornton (2009)
constructed a parameterization of γN2O5 as a function of
aerosol liquid water, nitrate, and chloride content based on the
measurements of laboratory-generated internally mixed chloride–nitrate
particles. Similarly, ø was parameterized as a function of aerosol liquid
water content and aerosol chloride (Roberts et al., 2009).
These results have great implications for regional and global chemical transport
models that aim to improve the simulations of nitrate and ozone (Evans and Jacob, 2005;
Sarwar et al., 2014). However, the
field-derived values of γN2O5 and ø
often exhibit large inconsistencies with laboratory results, suggesting a
more complex nature of heterogeneous N2O5 uptake in the ambient
atmosphere (Brown et al., 2006; Chang et al., 2011).
N2O5 and NO3 can be measured by various different
techniques,
which have been summarized in Chang et al. (2011). For
example, N2O5 can be derived from thermal equilibrium with
NO2 and NO3 that are simultaneously measured by differential
optical absorption spectroscopy (DOAS; Platt and
Stutz, 2008; Stutz et al., 2004). Another indirect measurement of
N2O5 is subtracting ambient NO3 from the total measured
NO3 after converting N2O5 to NO3 in a heated inlet and
then detected by cavity ring-down spectroscopy (CRDS), cavity-enhanced
absorption spectroscopy (CEAS), or laser-induced fluorescence (LIF; O'Keefe and Deacon, 1988; Brown et al., 2001; Smith et al., 1995; Wood et
al., 2003; Stutz et al., 2010). Simultaneous indirect measurements of
N2O5 and NO3 can be implemented using thermal dissociation–chemical ionization mass
spectrometer (TD–CIMS) with high sensitivity and
time resolution (Stutz et al., 2004), although the
interference of m/z 62 (NO3) from the thermal decomposition of
peroxy acetyl nitrate (PAN) and other related species needs to be considered
(Wang et al., 2014). Recently, the CIMS using iodide
reagent ions (I-CIMS) with an unheated inlet configuration allowed for direct
measurements of N2O5 (Kercher et al., 2009; Tham et al.,
2014, 2016; Wang et al., 2016). The I-CIMS is also widely used to
measure ClNO2 in both laboratory and field studies (Thornton and
Abbatt, 2005; McNeill et al., 2006; Osthoff et al., 2008; Tham et al.,
2014, 2016; Wang et al., 2016). A large amount of ClNO2 was
first observed in polluted coastal regions owing to the abundant chloride
from sea salt aerosol, for example in the Gulf of Mexico and the Los Angeles
basin (Osthoff et al., 2008; Riedel et al., 2012; Kercher et al., 2009).
High levels of ClNO2 from anthropogenic chloride sources were also
reported in some inland areas (Thornton et al., 2010; Mielke et al.,
2011; Phillips et al., 2012, 2016; Bannan et al., 2015). More
recently some studies in Hong Kong (Tham et al., 2014; Brown et al.,
2016a; Wang et al., 2016) and in the North China Plain (NCP; Tham et al.,
2016; X. Wang et al., 2017; Z. Wang et al., 2017; Wang et al., 2018) observed
consistently high mixing ratios of N2O5 and ClNO2. In
particular, ClNO2 can be rapidly formed in the plumes of coal-fired
power plants in the NCP, which serves as an important source of chloride in
non-ocean regions. Besides these measurement efforts, recently, some
modeling studies have also evaluated the impacts of N2O5 and
ClNO2 chemistry on the ozone formation and regional air quality in
China (Xue et al., 2015; Wang et al., 2016; Li et al., 2016). Despite this,
our understanding of N2O5 and ClNO2 chemistry in highly
polluted urban regions with high levels of NOx, O3, and high
particulate matter is far from complete.
Beijing has been suffering from severe haze pollution during the last 2
decades (Chan and Yao, 2008). As a result, extensive studies
have been conducted to characterize the sources and formation mechanisms of
haze episodes (Huang et al., 2014; Guo et al., 2014; Li et al., 2017). The
results show that nitrate and its precursors have been playing increasingly
important roles in pollution events since 2006 mainly due to the continuous
decrease in SO2 (van der A et al., 2017). While the
formation mechanisms of nitrate are relatively well known, the relative
contributions of different mechanisms can have large variability and
uncertainties. Pathak et al. (2009) found that
the heterogeneous hydrolysis of N2O5 contributed 50 %–100 % of the
nighttime enhancement of nitrate concentration in Beijing. WRF-Chem model
simulations showed only 21 % enhancement of nitrate during highly polluted
days (Su et al., 2016). A recent study also observed a large nocturnal
nitrate formation potential from N2O5 heterogeneous uptake, which
is comparable to and even higher than that from the partitioning of
HNO3 in rural Beijing in autumn (H. Wang et al., 2017). A
large contribution of the heterogeneous hydrolysis of N2O5 to the
high PM2.5 nitrate, even in the daytime due to persistently high
NO2, was also reported in Hong Kong (Xue et al.,
2014a). All these results highlight the fact that N2O5 heterogeneous uptake
might be an important pathway of nitrate formation in Beijing. A recent
modeling study has evaluated the impacts of heterogeneous ClNO2
formation on next-day ozone formation in Beijing
(Xue et al., 2014b). However, the roles of
N2O5 in nitrate formation and of N2O5 and ClNO2
in nighttime and daytime chemistry in summer in urban Beijing during field
campaigns are not characterized yet, except for one measurement in suburban
Beijing in the summer of 2016 (Wang et al., 2018).
In this work, two high-resolution time-of-flight CIMSs using the same iodide
ionization system operated by the Institute of Atmospheric Physics
(IAP-CIMS) and University of Manchester (UoM-CIMS), respectively, were
deployed in urban Beijing for real-time measurements of gas-phase
N2O5 and ClNO2. A broadband cavity-enhanced absorption
spectrometer (BBCEAS) operated by the University of Cambridge was also
deployed synchronously for the intercomparison of N2O5. The
temporal variations of N2O5 and ClNO2 in summer and their
relationships are characterized. The heterogeneous N2O5 uptake
coefficients and ClNO2 production yields are estimated, and their
implications in nitrate formation are elucidated.
Experimental methods
Field campaign site and meteorology
The measurements were conducted during the Air Pollution and Human Health
(APHH) summer campaign from 11 to 16 June 2017 at the Institute of
Atmospheric Physics (IAP), Chinese Academy of Sciences (39∘58′28′′ N, 116∘22′16′′ E, 49 m a.s.l.), which is an
urban site located between the north 3rd and 4th ring roads in
Beijing. The meteorological variables including wind direction (WD), wind
speed (WS), relative humidity (RH), and temperature (T) at 15 and 100 m
were obtained from the Beijing 325 m meteorological tower (BMT) at the
sampling site. The hourly average RH ranged from 12.9 % to 82.8 %, with
an average value of 36.8±15.9 %, and the hourly average
temperature ranged from 17.9 to 38.7 ∘C averaged at 26.7±4.9 ∘C. All IAP instruments were deployed on the roof of a two-story
building (∼ 10 m), while UoM-CIMS and BBCEAS were
housed in two containers at ground level (∼ 4 m)
approximately 20 m away. More details about the sampling site can be found
in previous studies (Sun et al., 2012). All data in this study are reported in Beijing local
time.
Instruments
IAP-CIMS
Ambient air was drawn into the sampling room through ∼ 2 m
Teflon perfluoroalkoxy tubing (PFA; 1/4 inch inner diameters) at
a flow rate of 10 standard liters per minute (SLM), from which
∼ 2 SLM was subsampled into the CIMS. Methyl iodide gas
(CH3I) from a heated CH3I permeation tube cylinder (VICI,
170-015-4600-U50) was ionized by flowing through a soft X-ray ionization
source (Tofwerk AG, type P) under an ultrahigh-purity nitrogen (N2,
99.999 %) flow (2.5 SLM). This flow enters an ion molecule reaction (IMR)
chamber, which was maintained at a pressure of 200 mbar using an SH-112 pump
fitted with a Tofwerk blue pressure control box to account for changes in
ambient pressure. A short segmented quadrupole (SSQ) positioned behind the
IMR was held at a pressure of 2 mbar using a Tri scroll 600 pump. Note that
the voltage settings used for the guidance of ions were carefully tuned to
avoid declustering as much as possible (Lopez-Hilfiker et
al., 2016). The gas-phase background was determined once during the campaign
by passing dry N2 into the inlet for 5 min.
UoM-CIMS
The UoM-CIMS setup has been described elsewhere (Priestley et al., 2018); a Filter Inlet for Gases and AEROsols (FIGAERO; Lopez-Hilfiker et
al., 2014) was additionally used in this study. The gas-phase inlet of UoM-CIMS consisted
of 5 m 1/4′′ ID PFA tubing connected to a fast inlet pump
with a total flow rate of 13 SLM from which the ToF-CIMS subsampled 2 SLM.
CH3I gas mixtures in N2 were made in the field using a custom-made
manifold (Bannan et al., 2014). A total of 20 standard cubic centimeters per minute (SCCM) of the CH3I mixture was
diluted in 4 SLM N2 and ionized by flowing through a Tofwerk X-ray
ionization source. This flow enters into the IMR, which was maintained at a
pressure of 400 mbar using an SSH-112 pump also fitted with a Tofwerk blue
pressure control box, while the subsequent SSQ was held at a pressure of 2 mbar
using a Tri scroll 600 pump. During the campaign, gas-phase backgrounds
were established through regularly overflowing the inlet with dry N2
for 5 min continuously every 45 min as has been performed previously.
The ambient target molecules were first ionized by reagent ions in the IMR
and then detected as adduction products with iodide, for instance
ClNO2 as I⋅ClNO2- at m/z 208 and 210
(I⋅37ClNO2-), and N2O5 as
I⋅N2O5- at m/z 235
(Slusher et al., 2004; Kercher et al.,
2009) at a time resolution of 1 s. Data analysis is performed using the
“Tofware” package (version 2.5.11) running in the IGOR Pro (WaveMetrics, OR,
USA) environment. The mass axis of UoM-CIMS was calibrated using I-,
I2-, and I3-, while that of IAP-CIMS was
calibrated using NO3-, I-, I⋅H2O-, I⋅CH2O2-,
I⋅HNO3-, and I3- covering a wide range from
m/z 62 to 381. Examples of high-resolution peak fittings of m/z 208, 210, and 235
for IAP-CIMS are presented in Fig. S1 in the Supplement.
Broadband cavity-enhanced absorption spectrometer (BBCEAS)
A detailed description of BBCEAS has been given in Kennedy et al. (2011).
Briefly, ambient air is first heated to 140 ∘C to thermally dissociate
N2O5 into NO3 and then enters the observational cavity that
consists of two high-reflectivity mirrors. The sum of N2O5 and
NO3 is determined using the measured optical absorption of NO3 in
the wavelength of 640–680 nm. The temperature of the cavity is kept at 85±1 ∘C
to prohibit the recombination of NO3 and NO2 and
to maintain the stability of the optical transmission signal. A very fast
flow rate of 20 L min-1 is adopted to minimize the residence time of gases
through PFA tubes. The loss of NO3 through the system was estimated to
be approximately 10 %.
Considering that the relatively high aerosol loadings in Beijing can
attenuate the intracavity light intensity and thus deteriorate instrument
sensitivity, a poly tetrafluoroethylene (PTFE) filter of pore size 1 µm
was used to remove aerosol particles from the airstream. This filter also acts
a point loss (∼ 10 %) for NO3 but has a negligible
impact on N2O5 (Dube et al., 2006). Because the mixing ratio of
N2O5 is higher than NO3 by a factor of >10 during
the APHH summer campaign, the influence of filter loss on the measurements of
N2O5 + NO3 is expected to be small. Aging of aerosol
particles on the filter may potentially introduce uncertainties for the
transmission efficiencies of NO3 and N2O5, but was found to
be insignificant in this study.
Calibrations and intercomparisons
During the campaign, field calibrations for UoM-CIMS were regularly carried
out using known concentration formic acid gas mixtures made in the
custom-made manifold. A range of other species were calibrated after the
campaign, and relative calibration factors were derived using the measured
formic acid sensitivity during these calibrations as has been performed
previously (Le Breton et al., 2014, 2017; Bannan et al., 2014, 2015).
The UoM-CIMS was calibrated post-campaign for both N2O5 and
ClNO2 relative to formic acid that was calibrated and measured
throughout the campaign. This is completed assuming that the ratio between
formic acid and ClNO2 sensitivity remains constant. ClNO2 was
calibrated using the method described in Kercher et al. (2009). Briefly, a stable source of N2O5 is generated and passed
over a salt slurry in which excess chloride reacts to produce gaseous
ClNO2. The N2O5 for this process was synthesized based on the
methodology described by Le Breton et al. (2014). Excess O3 is
generated through flowing 200 SCCM O2 (BOC) through an ozone generator
(BMT, 802N) into a 5 L glass volume containing NO2
(Sigma-Aldrich, >99.5 %). The outflow from this reaction vessel is cooled in a
cold trap held at -78 ∘C (195 K) by a dry ice–glycerol mixture
in which N2O5 is condensed and frozen. The trap is allowed to reach
room temperature and the flow is reversed whereby it is then condensed in a
second trap held at 220 K. This process is repeated several times to purify
the mixture. The system is first purged by flowing O3 for 10 min
before usage. To ascertain the N2O5 concentration in the line, the
flow is diverted through a heated line to decompose the N2O5 and
into to a Thermo Scientific 42i NOx analyzer in which it is detected as
NO2. According to the intercomparisons with the BBCEAS, including this
study and others (e.g., Le Breton et al., 2014; Bannan et al., 2017), the possible interference of NOy on the
NOx analyzer is not deemed important in terms of our reported
N2O5 concentrations.
ClNO2 was produced by flowing a known concentration of N2O5
in dry N2 through a wetted NaCl scrubber. Conversion of N2O5
to ClNO2 can be as efficient as 100 % on sea salt, but it can also be
lower, for example if ClNO2 is converted to Cl2 (Roberts et al.,
2008). In this calibration we have followed the accepted methods of
Osthoff et al. (2008) and Kercher et al. (2009) that show a conversion yield of 100 % and have assumed this yield
in the calibrations of this study.
The second method used to verify our ClNO2 calibration is cross-calibration with a turbulent flow tube chemical ionization mass spectrometer
(TF-CIMS; Leather et al., 2012). A known concentration of
0–20 SCCM Cl2 (99.5 % purity Cl2 cylinder, Aldrich) from a
diluted (in N2) gas mix is flowed into an excess constant flow of
20 SCCM NO2 (99.5 % purity NO2 cylinder, Aldrich) from a diluted
(in N2) gas mix, to which the TF-CIMS has been calibrated. This flow is
carried in 52 SLM N2 that is purified by flowing through two heated
molecular sieve traps. This flow is subsampled by the ToF-CIMS in which the
I⋅ClNO2- adduct is observed. The TF-CIMS is able to
quantify the concentration of ClNO2 generated in the flow tube as the
equivalent drop in NO2- signal. This indirect measurement of
ClNO2 is similar in its methodology to ClNO2 calibration by
quantifying the loss of N2O5 reacted with Cl- (e.g.,
Kercher et al., 2009). The TF-CIMS method gives a calibration factor 58 % greater than
that of the N2O5 synthesis method; therefore this is taken as our
measurement uncertainty. This calibration was scaled to those in the field
using formic acid calibrations carried out in the laboratory by overflowing
the inlet with various known concentrations of gas mixtures
(Bannan et al., 2014).
Time series of (a–b) meteorological parameters (WS, WD, RH, T) and
surface area density (Sa), (c) trace gases (O3, NO, NO2),
and (d–e) IAP-CIMS species (N2O5, ClNO2). The UoM-CIMS and BBCEAS
measurements are also shown for intercomparison. The four nights (i.e.,
P1, P2, P3, and P4) are marked for further discussions.
The IAP-CIMS calibration for N2O5 was performed by comparing with
the measurements from the BBCEAS. As shown in Fig. S2, the raw signals of
N2O5 from the IAP-CIMS measurements were highly correlated with
those from BBCEAS (R2=0.84). Given that the intercomparison
between the two instruments was relatively constant throughout the study,
the average regression slope of 0.54 was then applied to determine the
mixing ratio of N2O5 for the IAP-CIMS. The estimated
N2O5 mixing ratios were then compared with those measured by
UoM-CIMS. As shown in Fig. 1, the two N2O5 measurements tracked
well with each other (R2=0.84, slope = 1.42) although some
differences at midnight on 13 June were observed. The raw signals of
ClNO2 given by the IAP-CIMS were first converted to mixing ratios by
assuming the same sensitivity between ClNO2 and N2O5 (i.e.,
0.54 cps pptv-1). The results show that the estimated ClNO2 for
the IAP-CIMS agrees well with that measured by UoM-CIMS and calibrated
post-campaign (R2=0.93, slope = 0.905, Fig. 1). Overall, the
uncertainty is 17 % and 58 %, and the detection limit is 1.7 and 0.7 pptv
for N2O5 and ClNO2 of IAP-CIMS, respectively. All the
discussions below are based on IAP-CIMS measurements unless otherwise
stated.
Collocated measurements
An Aerodyne high-resolution time-of-flight aerosol mass spectrometer (HR-AMS
hereafter) and an Aethalometer (AE33, Magee Scientific Corp.) were deployed
on the roof of the two-story building to measure size-resolved
non-refractory submicron aerosol (NR-PM1) species with a time
resolution of 5 min, including organics (Org), sulfate
(SO42-), nitrate (NO3-), ammonium
(NH4+), chloride (Cl-) (DeCarlo et al.,
2006; Canagaratna et al., 2007), and black carbon (BC). A more
detailed description of the operations and calibrations of this HR-AMS can
be found in Xu et al. (2015) and Sun et al. (2016). Other collocated
measurements in two containers at ground level included gaseous species of
O3 (TEI 49C UV absorption analyzer), NO (TEI 42i TL NO analyzer), and
NO2 (CAPS NO2 monitor, Aerodyne Research Inc.) and size-resolved
particle number concentrations (11–550 nm) by a scanning mobility particle
sizer (SMPS) equipped with a long differential mobility analyzer (DMA, TSI,
3081A) and a condensation particle counter (CPC, TSI, 3772).
Data analysis
Estimation of γN2O5
NO3 is formed from the reaction of NO2 with O3 (Reaction R1) with a
temperature-dependent reaction rate constant k1. NO3
rapidly photolyzes during daytime, but at night it reacts with NO2 to
produce N2O5 (Reaction R2). N2O5 can thermally decompose back to
NO3 and NO2, and the equilibrium rate coefficient Keq is a function of ambient temperature. In this study,
values of k1 and Keq recommended by Atkinson et al. (2004) and Brown and Stutz (2012) were used. The indirect loss of
N2O5 is mainly through reactions of NO3 with either NO or
VOCs (Reaction R3), while direct N2O5 loss is predominantly from the
heterogeneous hydrolysis on the surface of aerosol particles that contain
water (Reaction R4) or chloride (Reaction R5). Note that “het” is an abbreviation of
heterogeneous in the equations. The net reaction of Reactions (R4) and (R5) can be
described as Reaction (R6) where
kN2O5 is the
heterogeneous uptake rate of N2O5, and ø is the
ClNO2 yield.
NO2+O3→NO3+O2,k1NO2+NO3+M↔N2O5+M,KeqNO3+(NO or VOCs)→products,kNO3N2O5+H2O(het)→2HNO3(aq)N2O5+Cl-(het)→NO3-(aq)+ClNO2N2O5+(H2OorCl-)(het)→(2-ø)NO3-(aq)+øClNO2,kN2O5
When the uptake reaction was not limited by gas-phase diffusion,
kN2O5 can be
simplified as Eq. (1) (Riemer et al., 2003; Dentener and Crutzen,
1993):
kN2O5=14×c×Sa×γN2O5,
where c is the mean molecular speed of N2O5 (unit, m s-1),
and Sa is the aerosol surface area density calculated from the
size-resolved particle number concentrations assuming spherical particles
(unit, µm cm-3). Note that Sa determined under dry
conditions was converted to that under ambient RH levels by using the
hygroscopic growth factor in Liu et al. (2013).
The nocturnal mixing ratio of NO3 can be derived from
simultaneous measurements of NO2 and N2O5 (Reaction R2) assuming
that the equilibrium between NO3 and N2O5 is rapidly
established after sunset (Brown et al., 2003a).
[NO3(cal)]=[N2O5]Keq[NO2]
The nitrate radical production rate p(NO3) can be calculated from
Reaction (R1) assuming that the nitrate radical is solely from Reaction (R1).
p(NO3)=k1[NO2][O3]
With a steady-state assumption for NO3 and N2O5, the inverse
N2O5 steady-state lifetime, τ(N2O5)-1,
which is defined as the ratio of p(NO3) to the N2O5 mixing
ratios, can be expanded to Eq. (4) after the substitution of Eqs. (2) and
(3) into the approximate time change rate for N2O5 (Brown et al., 2003a).
τ(N2O5)-1=p(NO3)[N2O5]≈kNO3Keq[NO2]+kN2O5
kNO3Keq[NO2] represents the
contribution to τ(N2O5)-1 from the indirect
N2O5 loss pathway, i.e., through NO3 reactions with VOCs
and NO, while kN2O5
indicates the direct loss of N2O5 through heterogeneous uptake.
Considering that the production of ClNO2 is predominantly from
heterogeneous N2O5 uptake within stable air masses and
precursors, the production rate of ClNO2 (pClNO2) can be related to
the heterogeneous loss rate of N2O5 by
pClNO2=dClNO2dt=ø×14×c×Sa×γN2O5.
The production rate of particulate nitrate (pNO3-) was obtained
from HR-AMS measurements assuming that the measured pNO3- was
totally from the production of nitrate by Reaction (R4) (Phillips et
al., 2016). Note that the formation of particulate nitrate from regional
transport or via the net uptake of HNO3 to aerosol is not taken into
consideration.
pNO3-=dNO3-dt=(2-ø)×14×c×Sa×γN2O5
Only periods with concurrent nighttime formation of ClNO2 and
NO3- meet the requirement that both are produced only
from heterogeneous N2O5 uptake. By combining Eq. (5) with Eq. (6), γN2O5 and
ø can be represented as follows.
γN2O5=2(pClNO2+pNO3-)c×Sa×[N2O5]ø=2pNO3-pClNO2+1-1
Parameterization of γN2O5 and ø
Aerosol liquid water content associated with inorganic species was estimated
using the ISORROPIA-II thermodynamic equilibrium model (Nenes et al.,
1998; Fountoukis and Nenes, 2007), with input data of ambient NR-PM1
species, and RH and T at 15 m. The N2O5 uptake coefficient and
ClNO2 yield can also be calculated by the parameterization proposed by
Bertram and Thornton (2009).
γN2O5=Ak1-11+29[Cl-][NO3-]+0.06[H2O][NO3-]
ø=1+[H2O]483[Cl-]-1
[H2O], [NO3-], and [Cl-] are molar concentrations of liquid water, particle nitrate, and chloride,
respectively, and the empirical parameters A =3.2×10-8 and
k=1.15×106×(1-e-0.13[H2O]) are used.
Results and discussion
Overview of N2O5 and ClNO2 measurements
Figure 1 shows the time series of N2O5 and ClNO2, gaseous
species of NO, NO2, and O3, and meteorological parameters during
the field campaign. Both N2O5 and ClNO2 exhibited large
day-to-day variability with the 5 min average (±1σ) mixing
ratios being 79.2±157.1 and 174.3±262.0 pptv,
respectively. Such dramatic variations of N2O5 and ClNO2
are consistent with previous observations in various environments, for
example at ground sites in Colorado and London (Bannan et al.,
2015; Thornton et al., 2010) and the residual layer at Mt. Tai
(Z. Wang et al., 2017). Four nights (i.e., P1, P2, P3, and P4 from
20:00 to 04:30) were selected to investigate the nocturnal chemistry of
N2O5 and ClNO2 in this study. The first two nights (P1 and
P2) showed much higher mixing ratios of N2O5 and ClNO2 than
those during P3 and P4, although the NOx and O3 levels during P4
were comparable to those during P2 (Table 1).
Summary of average (±1σ) meteorological parameters
(RH, T, WS), CIMS species (N2O5, ClNO2), the calculated
NO3, nitrate radical production rate p(NO3), N2O5
reactivity (τ(N2O5)-1) and NO3 reactivity (τ(NO3)-1), trace gases (O3, NO2, NO), and NR-PM1
species (NO3-, Cl-) for the entire study and four nighttime
periods (i.e., P1, P2, P3, and P4).
Entire
P1
P2
P3
P4
Meteorological parameters
RH (%)
36.8±15.9
36.3±5.5
41.3±2.5
60.5±6.5
28.0±7.0
T (∘C)
26.7±4.9
24.5±1.1
23.2±0.7
23.2±1.4
29.4±2.4
WS (m s-1)
2.9±1.4
1.9±0.9
2.3±0.7
1.9±0.6
3.7±1.7
CIMS species
N2O5 (pptv)
79.2±157.1
176.2±137.2
515.8±206.4
37.8±29.0
88.3±68.2
ClNO2 (pptv)
174.3±262.0
427.3±222.5
748.3±220.6
227.7±103.7
57.2±39.0
NO3(cal) (pptv)
8.9±15.7
7.2±7.3
48.1±26.2
2.0±2.3
18.2±15.2
p(NO3) (ppbv h-1)
3.2±2.3
3.6±4.2
2.8±0.5
1.7±1.2
2.6±1.4
τ(N2O5)-1 (s-1)
0.011±0.017
0.014±0.028
0.0016±0.0008
0.014±0.0063
0.016±0.011
τ(NO3)-1 (s-1)
0.34±0.87
0.62±1.66
0.021±0.017
0.42±0.21
0.29±0.30
Gaseous species
O3 (ppbv)
51.1±35.4
23.4±23.2
55.6±5.3
17.8±15.3
40.3±28.0
NO2 (ppbv)
28.1±17.1
56.2±22.4
16.9±3.9
38.2±9.9
28.7±16.0
NO (ppbv)
8.7±16.9
15.6±14.6
0.5±0.7
2.3±3.5
7.1±13.3
NR-PM1 species
NO3- µg m-3
2.7±2.4
2.3±1.5
4.3±0.7
4.3±1.6
0.6±0.2
Cl- µg m-3
0.10±0.16
0.13±0.14
0.09±0.02
0.08±0.09
0.04±0.07
The highest N2O5 mixing ratio (1.10 ppbv, 5 min average) was
observed at 02:15 on 13 June (P2), which is comparable to the previous
observation in urban Beijing (1.3 ppbv; H. Wang et al., 2017),
but much lower than that in the aged air masses in Hong Kong at ∼ 7.8 ppbv (Brown et al., 2016b). A recent measurement at a suburban site
in Beijing impacted by the outflow of urban Beijing air masses also reported
consistently high N2O5 (1 min maxima 937 pptv; Wang et al., 2018). The mixing ratio of N2O5 was
also much higher than that in the nocturnal residual boundary layer at Mt.
Tai (167 pptv; Z. Wang et al., 2017), indicating potentially
significant nighttime N2O5 chemistry in highly polluted urban
areas. One of the reasons for this could be the high mixing ratios of
precursors; for instance, the average O3 mixing ratios at nighttime
were as high as 18–56 ppbv. The maximal N2O5 that occurred
during P2 rather than the rest of the nights was likely due to insignificant
titration of NO during P2, e.g., 0.5 vs. 2.3–15.6 ppbv. The lowest nighttime
average of N2O5 (∼ 37.8 pptv) was observed during P3
although the NO2 showed a much higher concentration than those during P2
and P4, indicating the joint influences of precursors (NO2 and
O3). Fast heterogeneous hydrolysis of N2O5 under high RH (∼ 60.5 %) conditions during P3 could be another
reason, which was supported by the higher ClNO2 during P3 than P4.
Similar to N2O5, ClNO2 presented the highest value
(1.44 ppbv, 5 min average) before sunrise on 13 June (P2), yet it is lower than
the maximum of 2.1 ppbv (1 min average) observed at a rural site located
to the southwest of Beijing (Tham et al., 2016) and also the
ClNO2 peak of 2.9 ppbv (1 min average) in suburban Beijing
(Wang et al., 2018). These results indicated ubiquitously
observed ClNO2 in the NCP, although high ClNO2 mixing ratios
have also been previously observed in both marine and continental
environments in North America, Europe, and Asia (Osthoff et al.,
2008; Mielke et al., 2011; Thornton et al., 2010; Phillips et al., 2012; Tham et
al., 2014). The average nitrate radical production rate p(NO3) was 2.8 and 3.6 ppbv h-1
during P1 and P2, respectively, which
are both higher than those during P3 and P4 (1.7–2.6; Table 1). This result
supports a higher production potential for N2O5 during P1 and
P2. On average, p(NO3) was 2.6±2.4 ppbv h-1 at nighttime,
indicating more active nocturnal chemistry than previous studies in NCP in
terms of radical production rates, for example 1.2±0.9 ppbv h-1 in
suburban Beijing, 1.7±0.6 ppbv h-1 in Wangdu, and
0.45±0.40 ppb h-1 at Mt. Tai (Tham et al., 2016; Z. Wang et al., 2017; Wang et al., 2018). We also note that the p(NO3) was comparable
between P4 and P2 (2.6 vs. 2.8 pptv), yet the N2O5 and
ClNO2 mixing ratios during P4 were much lower, likely due to the
difference in NO levels, i.e., 0.5 vs. 7.1 ppbv. The favorable dispersing
meteorological conditions with higher wind speed and lower relative humidity
in P4 than in P2 might also be an explanation (Table 1). Our results
illustrate that precursors levels, reaction rates, and meteorological
conditions can all affect the variability of N2O5 and ClNO2.
Diurnal variations of trace gases (NO, NO2, O3),
IAP-CIMS species (N2O5, ClNO2), nitrate radical
production rate p(NO3), and NR-PM1 species (Cl-,
NO3-).
The average diurnal variations of trace gases, N2O5,
ClNO2,
and submicron nitrate and chloride are depicted in Fig. 2. O3 showed a
pronounced peak of 93.3 ppbv between 14:00 and 16:00 corresponding to a
minimum mixing ratio of NO2 (9.1 ppbv). As a consequence, p(NO3)
showed relatively high values around noon with a decrease in the middle of
the afternoon owing to the depletion of NO2 and then reached a
maximum of 5.9 ppbv h-1 before sunset. A similar diurnal pattern of
p(NO3) was also observed at a rural site in the autumn in Beijing
(H. Wang et al., 2017). Both NO and NO2 showed pronounced
diurnal cycles with lowest concentrations in the afternoon. In addition to
the rising boundary layer, the formation of NOz is another important
reason for the low levels of NOx during this time period in urban
Beijing (Sun et al., 2011). Nitrate and chloride
also showed lowest concentrations in the late afternoon, mainly due to the
evaporative loss under high temperature conditions (Sun et
al., 2012).
(a–b) Average reactivity of N2O5 (τ(N2O5)-1) and NO3 (τ(NO3)-1) for
different nights (i.e., P1, P2, P3, and P4). The error bar represents the
standard deviation. (c) Variations of the nocturnal τ(N2O5)
as a function of aerosol surface area density (Sa) and (d) variations of
the nocturnal τ(N2O5) as a function of relative humidity
(RH). The data were binned according to Sa (50 µm2 cm-3
increment) or RH (5 % increment). Mean (triangle), median (horizontal
line), 25 and 75th percentiles (lower and upper box), and
10 and 90th percentiles (lower and upper whiskers) are shown for
each bin.
N2O5 was rapidly formed after sunset. The mixing ratio of
N2O5 peaked approximately at 22:00 and then remained at a
consistently high level (∼ 200–300 pptv) until 03:00. After
that, N2O5 showed a rapid decrease due to significant
titration by NO. Similar loss of N2O5 due to the injection of
NO-containing air was also reported at sites near urban areas
(Brown et al., 2003b). Because NO is predominantly from local
emissions as supported by the tight correlation (R2=0.64–0.73,
Fig. S3) with black carbon, a tracer for combustion emissions, our results
demonstrated that local NO emissions serve as an important scavenger of
N2O5 before sunrise in urban Beijing. In comparison, the decrease
in N2O5 due to NO titration only occurred during the second
half of the night with low O3 in suburban Beijing (Wang et
al., 2018). This study also found high N2O5 after midnight due to
the incomplete titration of O3, for instance ∼ 52.9 ppbv
after midnight on 13 June, which is different from previous findings that
high N2O5 mixing ratios were typically observed before midnight
due to the rapid depletion of O3 (H. Wang et al., 2017; Z. Wang et al., 2017). The high
nocturnal mixing ratios of O3 and NO2 (Fig. 2)
highlight much higher oxidative capacity at night in summer in urban Beijing
compared to the other seasons and/or rural locations.
ClNO2 showed clear nocturnal formation from heterogeneous processing
and decreased rapidly after sunrise, mainly due to photolysis (Fig. 2). Note
that ClNO2 peaked at a similar time (21:00–22:00) as that of
N2O5 without showing a time lag of 1–3 h as previously observed in
Jinan (X. Wang et al., 2017), indicating that either particulate
Cl- was sufficient for the heterogeneous reactions or other chlorine
sources (e.g., HCl) contributed to the formation of ClNO2 in urban
Beijing. According to previous studies, the partitioning of HCl to
particulate Cl- could substantially contribute to ClNO2 formation
at urban sites (Thornton et al., 2010; Riedel et al., 2012). In
addition, Wang et al. (2018) also speculated that large
particulate chloride during the campaign was possibly replenished by
gas-phase HCl due to high emissions from human activities. We also found
that ClNO2 was well correlated with chlorine (Cl2) derived from
IAP-CIMS (R2=0.90–0.99) rather than particulate chloride
(Cl-) (R2=0.01–0.44) at nighttime, indicating that
ClNO2 might act as an intermediate during the formation of Cl2
under sufficient chloride conditions (Roberts et al., 2008).
Indeed, the much lower particulate Cl- than ClNO2 also indicated other chlorine sources. Therefore, we need simultaneous
measurements to further support such a conclusion in this study, e.g.,
HCl.
Correlations between ClNO2 and N2O5 for four
different nights, i.e., P1, P2, P3, and P4. The data are color coded by the
hours since sunset. Also shown are the correlation coefficients and slopes.
Reactivity of N2O5 and NO3
Considering the time needed to meet the steady-state assumption, only
the data 2 h after sunset were used to calculate N2O5
steady-state lifetime via Eq. (4) (Wagner et al., 2013). High
N2O5 reactivity was observed and the average τ (N2O5)-1
was 0.16–1.58×10-2 s-1 during these four nights corresponding to a short nighttime
N2O5 lifetime between 1.1 and 10.7 min (Fig. 3), with τ(N2O5)-1
ranging from 0.20 × 10-2 to
1.46 × 10-2 s-1 throughout the campaign. Such values are
overall consistent with those measured at surface sites and in the nocturnal
residual layer in NCP, for example 1.30 × 10-2 s-1 in
Wangdu (Tham et al., 2016) and 1.30–1.40 × 10-2 s-1 at
Mt. Tai (Z. Wang et al., 2017). In comparison, the
N2O5 loss is much more rapid than that previously reported in
southern China (1–5 h; Brown et al., 2016b) and the USA (a few hours; Wagner et al., 2013), mainly due
to the high aerosol loading in NCP leading to an enhanced N2O5
sink through both indirect and direct pathways. Correspondingly, the average
τ(NO3)-1 values calculated from the inferred NO3 were
0.02–0.62 s-1 during the four nights, indicating active NO3
nighttime chemistry through reactions with NO and VOCs in the polluted
nocturnal boundary. Note that P2 and P4 showed comparable p(NO3) (2.8
vs. 2.6 ppbv h-1; Table 1), yet the N2O5 reactivity during
P4 (1.58 × 10-2 s-1) was significantly higher than that
during P2 (0.16 × 10-2 s-1), likely due to the higher NO
level, and the enhanced N2O5 heterogeneous loss might also be an
explanation. Consistently, τ(NO3)-1 showed similar
patterns to τ(N2O5)-1. Indeed, the
N2O5 reactivity presented a nonlinear dependence on aerosol
surface area (Sa) and relative humidity (Fig. 3c and d). Although P3
showed much higher RH than P4 (60.5 % vs. 28.0 %), the N2O5
reactivity was comparable between P3 and P4 (0.014 vs. 0.016 s-1),
illustrating the complex heterogeneous process of N2O5.
Box plots of (a) Org / SO4 ratio, (b) LWC,
(c) particulate chloride, (d) particulate nitrate, and (e) ClNO2/N2O5 ratio for each night,
i.e., P1, P2, P3, and P4. The mean (triangle), median (horizontal line), 25 and 75th
percentiles (lower and upper box), and 10 and 90th percentiles
(lower and upper whiskers) are shown.
Figure 3c shows the N2O5 lifetime as a function of surface area
density (Sa) with the data being binned according to the
50 µm2 cm-3Sa increment. τ(N2O5) decreased
rapidly from 11.8 to 2.2 min as Sa increased up to 500 µm2 cm-3 and then remained at relatively constant
levels at Sa>500 µm2 cm-3. Such an
Sa dependence of τ(N2O5) is consistent with previous
observations in Hong Kong (Brown et al., 2016b). Large variations in
τ(N2O5) as a function of RH were also observed. As shown in
Fig. 3d, the N2O5 lifetime decreased by nearly a factor of 5 from
11.3 to 2.2 min as RH increased from 40 % to 50 %. We noticed that
the aerosol surface area exhibits an increase as a function of RH at RH > 40 % (Fig. S4). These results suggested that the decrease in
τ(N2O5) at high RH levels (RH > 40 %) might be
caused by increased N2O5 uptake rates due to the higher Sa. In
addition, the increasing aerosol liquid water content at high RH might be
another reason (Fig. S4). Comparatively, the N2O5 lifetime showed
an increase as a function of RH at RH < 40 %, while the variations
in Sa were small, suggesting additional contributions from other
factors, for example aerosol loading and composition
(Morgan et al., 2015). Considering that the
period of this study is relatively short, long-term measurements are needed
in future studies to better characterize the parameterizations of τ(N2O5) as a function of Sa and RH.
Relationship between N2O5 and ClNO2
Previous studies have found that N2O5 and ClNO2 were
generally positively correlated in predominantly continental air masses,
whereas they were negatively correlated in marine air masses with high
chloride content (Bannan et al., 2015). Phillips et al. (2012) also reported large
variability in N2O5 and ClNO2 correlations and ClNO2/N2O5 ratios in air masses from continental or
marine origins due to the changes in particle Cl-. In this study,
ClNO2 was well and positively correlated with N2O5 during
all four nights (Fig. 4, R2=0.36–0.78), and only slight changes
in ClNO2/N2O5 ratios were observed after sunset. These
results are different from previous observations showing large variability
in the correlations (Osthoff et al., 2008), which
indicates that there are sufficient chloride sources for
ClNO2 formation during this study period. The differences in regression
coefficients among the four nights can be explained by different air masses
originating from different regions, which were calculated using the Hybrid
Single-Particle Lagrangian Integrated Trajectory (HYSPLIT; NOAA) model
(Draxler and Hess, 1997; Fig. S5). For example, ClNO2 tracked
much better with N2O5 after midnight (R2=0.69)
than before midnight (R2=0.16) during P2 (Fig. S6),
suggesting the influence of air masses from different regions (Fig. S5).
Comparatively, P4 and P1 showed similar tight correlations between
ClNO2 and N2O5 before and after midnight, consistent with
their similar back trajectories during the two different periods.
The ClNO2/N2O5 ratios varied significantly throughout the
study ranging from 0.3 to 95.5 (30 min average). The average (±1σ) ratio of ClNO2/N2O5 was 6.9±7.4,
consistent with previous studies in NCP, for example 0.4–131.3 in Jinan
and Wangdu (X. Wang et al., 2017; Tham et al., 2016). However, the ratios
are substantially higher than those measured in other megacities, e.g., Hong
Kong (0.1–2.0; Wang et al., 2016), London (0.02–2.4; Bannan et al.,
2015), and Los Angeles, California (0.2–10.0; Mielke et al., 2013). These
results indicate ubiquitously high ClNO2/N2O5 ratios in the
NCP, consistent with another measurement in suburban Beijing
(Wang et al., 2018), which might result from the high
ClNO2 production rate due to high aerosol loadings. We also note that
the relatively low N2O5 associated with high N2O5
reactivity might be another possible explanation. Furthermore, we compared
the ClNO2/N2O5 ratios with particulate concentrations and
compositions during the four nights (Fig. 5). P3 showed the highest median
ratio of 9.4, which is much higher than during the other three
nights (1.0–3.2). This can be explained by the correspondingly high liquid
water content that facilitated N2O5 heterogeneous uptake
(Morgan et al., 2015). In comparison, the
particle chloride concentrations were relatively close during the four
nights, with slightly lower concentrations during P4, further supporting
the fact that the ClNO2/N2O5 ratios were independent of particle
chloride in this study due to the sufficient chloride source for
ClNO2 production, e.g., HCl gas–particle partitioning. The lower
ClNO2/N2O5 ratios during P2 compared with P1 can be explained
by the “nitrate effect”, which suppressed N2O5 uptake
(Mentel and Wahner, 1999) as P2 showed much higher nitrate
concentrations than P1 (4.2 vs. 1.4 µg m-3). Note that the
ClNO2/N2O5 ratios were also characterized by a dependence
on Org / SO4 ratios in our campaign, similar to other studies
(Evans and Jacob, 2005; Riemer et al., 2009).
Time series of meteorological parameters (RH, T), particulate
nitrate (NO3-), mixing ratios of N2O5 and ClNO2,
and aerosol surface area density (Sa) for the selected periods on three
nights. The black solid lines are the predicted integration concentrations
of NO3- and ClNO2 calculated using the estimated
method.
N2O5 uptake coefficient and ClNO2 production
yield
To quantity the relative contributions of different pathways to
N2O5 loss, three periods with relatively stable air masses and
concurrent increases in ClNO2 and NO3- (Fig. 6; 20:00–23:00
on 12 June, 20:00–00:00 on 13 June, and 20:00–22:30 on 14 June) were
selected for the calculations of γN2O5 and ø. A rigorous
method as suggested by Phillips et al. (2016) was used in this
study. Briefly, the predicted concentrations of ClNO2 and NO3- were
derived by integrating pClNO2
and pNO3- with average Sa and N2O5 over each time step
(∼ 15 min) and initial estimations for γN2O5 and ø. The
integration was repeated by changing γN2O5 and ø until good
agreements between observed and predicted values of ClNO2 and NO3-
were reached. The derived heterogeneous uptake coefficient,
ClNO2 yield, and N2O5 loss rate kd following this method
are listed in Table 2.
Estimated uptake coefficient of N2O5, ClNO2
production yield, and related parameters for the selected periods on three
nights.
Period
RH (%)
γN2O5
ø
Kd (s-1)
Percentage
(%)
Case 1
39.9
0.017
0.35
0.00044
32.6
Case 2
63.6
0.090
0.10
0.0034
20.8
Case 3
21.1
0.019
0.15
0.00055
6.9
The estimated γN2O5 values for the three
selected periods were 0.017–0.09, which was generally comparable to previous
values (0.014–0.092) derived from the steady-state assumption method in the
NCP (H. Wang et al., 2017; X. Wang 2017; Z. Wang et al., 2017; Tham et al., 2016) and also consistent with recent measurements (0.012–0.055) using
the same method in suburban Beijing (Wang et al., 2018). However, the
γN2O5 determined
in our campaign was 1–2 orders of magnitude higher than
obtained in the laboratory (Thornton et al., 2003) and also
much higher than those in Hong Kong and Germany (Brown et al.,
2016b; Phillips et al., 2016). We also found that the parameterized γN2O5 values (0.0014–0.012)
determined from Eq. (9) (the Bertram–Thornton parameterization) were
significantly lower than the observed values, suggesting that more field
measurements are needed to improve the parameterization schemes. Note that
γN2O5 values appeared
to increase with rising relative humidity, which was also observed at
other sites (X. Wang et al., 2017; Thornton et al., 2003). For example,
γN2O5 values
increased from 0.019 to 0.090 when RH increased from 21.1 %
to 63.6 %. However, the γN2O5 values were
comparable at low RH levels (<40 %; 0.019 vs. 0.017 in Table 2)
although RH differed by a factor of 2 (21 % vs. 40 %). These results
further supported the fact that the influences of hygroscopic growth on γN2O5 were mainly caused by
increasing aerosol liquid water content. The direct N2O5 loss
rates estimated from the uptake coefficient were in the range of
0.00044–0.0034 s-1, which contributed 7–33 % to the total
N2O5 loss with the rest being indirect loss. The uncertainty of
the direct N2O5 loss rate contributions is estimated to be
∼ 40 %, associated with Sa (∼ 30 %),
O3 and NO2 (∼ 5 %), and N2O5
(∼ 17 %). Our results indicated that the fast N2O5
loss in the nocturnal boundary in urban Beijing was predominantly from the
indirect loss of NO3 rather than the heterogeneous uptake of
N2O5, mainly due to active NO3 reaction in summer. Such a
conclusion was different from previous results in autumn in Beijing that
found
N2O5 loss to be dominated by N2O5 heterogeneous hydrolysis
(69.1 %–98.8 %; H. Wang et al., 2017). Several studies
also revealed the importance of heterogeneous N2O5 uptake in
N2O5 loss in the NCP by using steady-state-derived γN2O5 (Tham et al.,
2016; X. Wang et al., 2017; Z. Wang et al., 2017). While the uncertainties in
different analysis methods, e.g., due to product formation rates or
the steady-state assumption, the high NO concentration
could be an important reason for the dominant N2O5 loss pathway.
The higher VOC emissions, particularly biogenic emissions (e.g., isoprene and
terpene), in summer than in other seasons might be another reason for the
differences in the dominant N2O5 loss pathway. Indeed, indirect
N2O5 loss via NO3 + VOCs was also found to dominate the total
loss of N2O5 (67 %) in summer in suburban Beijing
(Wang et al., 2018). Our results highlight significant
nighttime NOx loss through reactions of NO3 with VOCs in
summer in urban Beijing.
The ClNO2 yields ø derived for the three cases were 0.35, 0.10, and
0.15, respectively. The production yields in this study are substantially
larger than those in urban Jinan (0.014–0.082; X. Wang et al., 2017), yet
comparable to those reported at Mt. Tai (0.02–0.90; Z. Wang et al.,
2017) and continental Colorado (0.07–0.36; Thornton et al., 2010). However,
the significantly lower ø than that in suburban Beijing (0.50–1.0; X. Wang et
al., 2017) indicated more effective ClNO2 production in suburban
regions than urban regions to some extent. Indeed, the product of γN2O5 and ø (γN2O5×ø) in this study ranged from 0.006–0.009
and was much lower than in X. Wang et al. (2017; 0.008–0.035). We
noticed that ø values were much lower than those parameterized from Eq. (10)
(0.55–0.97), indicating that the Bertram–Thornton parameterization scheme
might overestimate the ClNO2 yield substantially. Note that γN2O5
might be overestimated, associated with an
underestimation of ø if assuming particulate nitrate is completely from
N2O5 heterogeneous uptake. Possible contribution from
gas-phase HNO3 repartitioning to the particulate phase was not
considered, mainly due to the lack of observational data for HNO3 and
NH3. Indeed, a recent study found that the nocturnal nitrate formation
potential by N2O5 heterogeneous uptake was comparable to that
formed by gas-phase HNO3 repartitioning in Beijing (H. Wang et al.,
2017). In addition, γN2O5×ø
was higher on 13 June than the other two days (e.g., 0.009 vs. 0.003–0.006),
which might explain the correspondingly higher ClNO2/N2O5 ratio on this
day (on average 8.2 vs. 1.2–1.4). Our
results overall suggest fast heterogeneous N2O5 uptake and a high
ClNO2 production rate in summer in urban Beijing, which might have
great implications for models to improve simulations for nocturnal
nitrate and daytime ozone.