Introduction
It has been well recognized that reactive nitrogen compounds, specifically
the nitrate radical (NO3) and dinitrogen pentoxide (N2O5),
play a key role in nighttime chemistry (Wayne et al., 1991; Brown and Stutz,
2012). NO3 is the most important oxidant in the nighttime and can be
considered the nighttime analogue of the hydroxyl radical (OH) for certain
volatile organic compounds (VOCs; Wayne et al., 1991; Benton et al., 2010). NO3 can initiate the
removal of many kinds of anthropogenic and biogenic emissions after sunset.
In NOx-rich plumes, NO3 is responsible for the vast majority of
the oxidation of biogenic VOCs because of its rapid reactions with
unsaturated hydrocarbons (Edwards et al., 2017). NO3 is predominantly
formed by the reaction of NO2 with O3 (Reaction R1) and further reacts with
NO2 to produce N2O5 (Reaction R2). N2O5 is rapidly
decomposed back to NO3 (Reaction R3), NO3, and N2O5 are in dynamic
equilibrium in the troposphere.
NO2+O3→NO3+O2NO2+NO3+M→N2O5+MN2O5+M→NO2+NO3+M
Photolysis of NO3 and the reaction of NO3 with NO are rapid, which
leads to a daytime NO3 lifetime being shorter than 5 s with extremely
low concentrations, whereas in low-NO air masses, the fate of NO3 is
mainly controlled by the mixing ratios of various VOCs and N2O5
heterogeneous hydrolysis because the two terms are the dominating loss
pathways of NO3 and N2O5. The VOC reaction is significant
downwind of an urban area or a strongly urban-influenced forested area in
summer. The NO3 oxidation of VOCs was responsible for more than 70 %
of nocturnal NO3 loss in Houston (Stutz et al., 2010) and contributed
approximately 50 % in a forest region in Germany (Geyer et al., 2001).
The reactions of NO3 with several biogenic VOCs (BVOCs) produce considerable amounts of
organic nitrates (ONs) with efficient yields, which act as important
precursors of secondary organic aerosols (SOAs). The reaction of NO3
with isoprene has a SOA mass yield of 23.8 % (Ng et al., 2008). For the
reaction with monoterpene, such as limonene, the SOA mass yield can reach
174 % at ambient temperatures (Boyd et al., 2017). The reactions of
NO3 + BVOCs are critical to the studies of aerosols on regional and
global scales (Fry et al., 2009; Rollins et al., 2009; Pye et al., 2010; Ng
et al., 2017). For example, ON had extensive percentages of fine particulate
nitrate (pNO3-) (34–44 %) in Europe (Kiendler-Scharr et
al., 2016).
The heterogeneous hydrolysis of N2O5 produces soluble nitrate
(HNO3 or NO3-) and nitryl chloride (ClNO2) on
chloride-containing aerosols (Reaction R4) (Finlayson-Pitts et al., 1989). This
reaction is known to be an important intermediate in the NOx removal
processes (Brown et al., 2006). The pseudo-first-order loss rate
constant of N2O5 via heterogeneous uptake is given in Eq. (1)
(Wahner et al., 1998).
N2O5+(H2O or Cl-)→(2-f)NO3-+fClNO2
kN2O5=0.25⋅c⋅γ(N2O5)⋅Sa
Here c is the mean molecule speed of N2O5, Sa is the aerosol
surface concentration, and γ (N2O5) is the N2O5
uptake coefficient. N2O5 heterogeneous hydrolysis is one of the
major uncertainties of the NO3 budget since the N2O5 uptake
coefficient can be highly variable and difficult to quantify (Brown and
Stutz, 2012; Chang et al., 2011; Wang and Lu, 2016). Laboratory and
field measurement studies have reported that the N2O5 uptake
coefficient has large variability and ranges from < 0.001 to 0.1;
the N2O5 uptake coefficient depends on relative humidity (RH),
particle morphology, compositions (water content, nitrate, sulfate, and organic
or mineral particles), and other factors (Wahner et al., 1998; Mentel et al.,
1999; Hallquist et al., 2003; Thornton et al., 2003, 2005;
Brown et al., 2006; Bertram and Thornton, 2009; Tang et al., 2012, 2014;
Gaston et al., 2014; Gržinić et al., 2015; Tang et al., 2017). The coupled
chemical mechanisms in ambient conditions are still not well understood.
ClNO2 forms and accumulates with a negligible sink during the night
and further photolyzes and liberates the chlorine radical (Cl) and
NO2
after sunrise. Hundreds of parts per trillion by volume to parts per billion by volume of ClNO2 can lead to several
parts per billion by volume of O3 enhancement and significant primary ROx production
(Osthoff et al., 2008; Thornton et al., 2010; McLaren et al., 2010; Riedel
et al., 2014; Sarwar et al., 2014; Tham et al., 2016).
Large amounts of NOx have been emitted for the past several decades in
China, but comprehensive field studies of the nighttime chemical processes
of reactive nitrogen oxides remain sparse. Previous studies have found high
mixing ratios of NO3 associated with high NO3 reactivity in the
megacities in China, including Shanghai, the Pearl River Delta (PRD), and
Beijing (Li et al., 2012; S. S. Wang et al., 2013; D. Wang et al., 2015). The
N2O5 concentration was elevated in Beijing (H. C. Wang et al.,
2017a, b) but was moderate in other parts of the North
China Plain (NCP), such as Wangdu, Jinan, and Mount Tai (Tham et al., 2016;
X. F. Wang et al., 2017; Z. Wang et al., 2017). Recently, the N2O5
uptake coefficients were determined to be very high, even up to 0.1 in the NCP,
but the reason is still not well studied (H. C. Wang et al., 2017b; X. F. Wang et al., 2017; Z. Wang et al., 2017). Reactive N2O5 chemistry
was also reported in Hong Kong and showed the highest field-observed
N2O5 concentration to date (Wang et al., 2016; Brown et al.,
2016). Observations and model simulations revealed that fast heterogeneous
uptake of N2O5 is an important pathway of pNO3-
formation in China (H. C. Wang et al., 2017b; Z. Wang et al., 2017; Su et al., 2017); the reaction also contributed
significantly to removal (Z. Wang et al., 2017; Brown et al., 2016).
Moreover, chlorine activation from N2O5 uptake had a significant
effect on daytime photolysis chemistry in China (Xue et al., 2015; Li et
al., 2016; Tham et al., 2016; T. Wang et al., 2016).
Map of Beijing and the surrounding area. The red star shows the
location of the Changping site, and red dots show other sites where previous
N2O5 measurements were conducted in the North China Plain (NCP),
including Wangdu, Jinan, and Mount Tai (Tai'an).
In this study, to quantify the contribution of NO3 and N2O5
chemistry to the atmospheric oxidation capacity and the NOx removal
process in the outflow of urban Beijing, we report the measurement of
N2O5, ClNO2, and related species in the surface layer of a
suburban site in Beijing and determine the N2O5 heterogeneous
uptake coefficients and ClNO2 yields. The nighttime NO3 oxidation
of BVOCs and its impact on ON formation in a NOx-rich
region were diagnosed. Finally, the nighttime NOx removal via NO3
and N2O5 chemistry was estimated and discussed.
Method
The site
Within the framework of a Sino-Sweden Joint Research Programme,
“Photochemical Smog in China”, a summer field campaign was conducted in
Beijing to enhance our understanding of secondary chemistry via
photochemical smog and heterogeneous reactions (Hallquist et al., 2016).
The data presented here were collected at a regional site, PKU-CP (Peking
University, Changping campus), from 23 May to 5 June 2016. The measurement
site is located in the northern rural area of Beijing, approximately
45 km
from the city center; the closest road is approximately 1 km to the south,
and there is no major industry in the surrounding areas (Fig. 1). The site is
surrounded to the north, east, and west by mountains. The general feature of
this site is that it captures air masses with strong influences from both
urban and biogenic emissions. Instruments were set up on the fifth floor of
the main building of the campus with inlets approximately 12 m above the
ground. Time is given in this paper as CNST (Chinese national standard time: UTC+8 h).
During the campaign, sunrise was at 05:00 CNST and sunset
was at 19:30 CNST.
The observed gas and particle parameters used in this analysis
during the campaign.
Species
Limit of detection
Methods
Accuracy
N2O5
2.7 pptv (1σ, 1 min)
CEAS
± 19 %
ClNO2
16 pptv (2σ, 1 min)
FIGAERO–ToF-CIMS
± 23 %
NO
60 pptv (2σ, 1 min)
Chemiluminescence
± 20 %
NO2
0.3 ppbv (2σ, 1 min)
Mo convert
± 50 %
O3
0.5 ppbv (2σ, 1 min)
UV photometry
± 5 %
Aerosol surface area
(4 min)
SMPS, APS
± 30 %
VOCs
0.1 ppbv (5 min)
PTR-MS
± 30 %
PM2.5
0.1 µgm-3 (1 min)
TEOM
± 5 %
PM1.0 components
0.15 µgm-3 (4 min)
HR-ToF-AMS
± 30 %
Instrument setup
A comprehensive suite of trace gas compounds and aerosol properties was
measured in the field study, and the details are listed in Table 1.
N2O5 was measured using a newly developed cavity-enhanced absorption
spectrometer (CEAS; H. C. Wang et al., 2017a). In the CEAS, ambient
N2O5 was thermally decomposed to NO3 in a perfluoroalkoxy
alkane (PFA) tube (length: 35 cm, I.D.: 4.35 mm) heated to 120 ∘C and was then detected within a PFA resonator cavity; the cavity was heated
to 80 ∘C to prevent NO3 reacting back to N2O5.
Ambient gas was sampled with a 1.5 m sampling line (I.D.: 4.35 mm) with a
flow rate of 2.0 Lmin-1. NO was injected for 20 s to destroy
NO3 from N2O5 thermal decomposition in a 5 min cycle, and
the corresponding measurements were then used as reference spectra. A Teflon
polytetrafluoroethylene (PTFE) filter was used in front of the sampling
module to remove ambient aerosol particles. The filter was replaced with a
fresh one every hour to avoid the decrease in N2O5 transmission
efficiency due to aerosol accumulation on the filter. The limit of detection
(LOD) was 2.7 pptv (1σ), and the measurement uncertainty
was 19 %.
ClNO2 and N2O5 were also detected using a time-of-flight
chemical ionization mass spectrometer (ToF-CIMS) with the Filter Inlet for
Gas and Aerosols (FIGAERO; Lopez-Hilfiker et al., 2014; Bannan et al.,
2015). Briefly, the gas-phase species were measured via a 2 m long,
6 mm outer-diameter PFA inlet while the particles were simultaneously
collected on a Teflon filter via a separate 2 m long, 10 mm outer-diameter
copper tubing inlet; both had flow rates of 2 Lmin-1. The gas phase
was measured for 25 min at 1 Hz, and the FIGAERO instrument was then
switched to place the filter in front of the ion molecule region; it was
then heated incrementally to 200 ∘C to desorb all the mass from
the filter to be measured in the gas phase, which resulted in
high-resolution thermograms. Formic acid calibrations were performed daily
using a permeation source maintained at 40 ∘C. Post-campaign
laboratory calibrations of N2O5 were first normalized to the
campaign formic acid calibrations to account for any change in sensitivity
(Le Breton et al., 2014). Then, ClNO2 measurements were quantified by
passing the N2O5 over a wetted NaCl bed to produce ClNO2. The
decrease in N2O5 from the reaction with NaCl was assumed to be
equal to the concentration of ClNO2 produced (i.e., 100 % yield). The
sensitivities of the CIMS to N2O5 and ClNO2 were found to be
9.5 and 1.2 ion counts per pptvHz-1, respectively, with errors of
23 and 25 % for ClNO2 and N2O5, respectively. The
LODs
for ClNO2 and N2O5 were 16 and 8 pptv, respectively. An
intercomparison of N2O5 measurements between the CEAS and
FIGAERO–ToF-CIMS showed good agreement; another paper on chlorine
photochemical activation during this campaign gives detailed intercomparison
results of N2O5 measured with the two different techniques (Le
Breton et al., 2018).
Submicron aerosol composition (PM1.0), including nitrate, sulfate,
chloride, ammonium, and organic compounds, were measured using a high-resolution
time-of-flight aerosol mass spectrometer (HR-ToF-AMS) (De Carlo et al., 2006;
Zheng et al., 2017). Particle number and size distribution (PNSD) were
measured with a scanning mobility particle sizer (SMPS, TSI 3936) and an
aerosol particle sizer (APS, TSI 3321) (Yue et al., 2009). The SMPS measured the
particles in the range between 3.5 and 523.3 nm in diameter, and the APS
measured the particles with a diameter range from 597.6 nm to 10.0 µm. Sa
was calculated based on the dry-state particle
number and geometric diameter in each size bin (3.5 nm–2.5 µm). Dry-state Sa was corrected to wet-particle-state Sa for
particle hygroscopicity by a growth factor. The growth factor, f(RH) = 1 + 8.77 × (RH/100)9.74, was derived from the measurement of
aerosol extinction as a function of RH in autumn in Beijing and is valid for
30 % < RH < 90 % (Liu et al., 2013). The uncertainty of
the wet aerosol surface areas was estimated to be ∼ 30 %,
associated with the error from the dry PNSD measurement (∼ 20 %)
and the growth factor (∼ 20 %). During this measurement,
fine particles below 500 nm contributed to more than 90 % of the total
Sa.
Time series of N2O5, ClNO2, and other relevant
parameters. The blue line in the O3 panel denotes the Chinese national air
quality standard for O3 (ca. 93 ppbv for the surface conditions). The
black line in the NO panel denotes 0.06 ppbv.
VOCs were measured by proton-transfer-reaction mass spectrometry (PTR-MS)
with a time resolution of 5 min (de Gouw and Warneke, 2007; Wang
et al., 2014). A commercial instrument (Thermo Fisher Scientific model 42i) equipped
with a molybdenum catalytic converter was used to monitor NOx. The LODs
were 60 pptv (1 min) for NO and 300 pptv (1 min) for NO2, with both at
a 20 % precision (Tan et al., 2017). The molybdenum catalytic technique
not only converts NO2 to NO but also converts ambient NOy such as
peroxyacetyl nitrate (PAN) and HNO3. Therefore, the measured
NO2
concentration corresponded to NO2 + NOy and was normally
higher than the real concentration, especially in an aged air mass with high
NOx conditions. In this study, we used a factor of 0.6 to
correct the nighttime NO2 concentration (a detailed explanation is in
the Supplement Sect. S1 and Fig. S1). The correction factor (0.6)
is the average of the correction factors during nighttime. The standard
deviation of the daytime correction factor for all the air masses
experienced at the Changping site was determined to be 0.27 (1σ). If
this uncertainty is extended to the nighttime correction factor, the
resulting uncertainty of the nighttime correction is 45 %. The uncertainty
of NO2 is 50 % when further including the associated measurement
uncertainty from calibrations. O3 was measured by a commercial
instrument using ultraviolet (UV) absorption (Thermo Fisher Scientific model 49i);
the LOD was 0.5 ppbv, with an uncertainty of 5 %. The mass concentration
of PM2.5 was measured using a standard tapered-element oscillating
microbalance (TEOM, 1400A analyzer). Meteorological parameters included
relative humidity, temperature, pressure, wind speed, and wind direction and
were available during the campaign. Photolysis frequencies were calculated
from the spectral actinic photon flux density measured with a
spectroradiometer (Bohn et al., 2008).
Results
Overview
During the campaign, the meteorological conditions of the site included high
temperature and low RH; the temperature ranged from 10 to 34 ∘C
and was 23 ± 5 ∘C on average, and RH
ranged from 10 to 80 %, with an average of 37 ± 15 %.
Because of the special terrain of the observation site, the local wind was
measured by the in situ meteorological stations; the site has a typical
mountain–valley breeze that cannot reflect the general air mass movement
patterns at slightly higher altitudes. Figure S2 shows the calculated
backward trajectories using the Hybrid Single-Particle Lagrangian Integrated
Trajectory (HYSPLIT) model (Draxler and Rolph, 2003). These images show the
24 h backward particle dispersion trajectories for 12:00 local time (CNST)
as the starting time during 23 May–5 July 2016. The arrivals of air
masses were mainly from the northwest and the south. Therefore, we
meteorologically separated the measurement period into two parts. The first
3 days show that the air masses came from the north or northwest; the
air masses represent the background region (defined as background air mass,
BAM). The air masses after 26 May originated from the polluted NCP and
passed over urban Beijing; they were characterized by large NOx
emissions and severe photochemical pollution (defined as urban air mass,
UAM).
Mean diurnal profiles of 5 × NO2, O3,
N2O5, 2 × NO3 (calculated), ClNO2, and
10 × pCl-. Panel (a) depicts the background air mass
(BAM) period and (b) depicts the urban air mass (UAM)
period.
The time series of N2O5, ClNO2, and other relevant species are
shown in Fig. 2, and nighttime statistical results are listed in Table S1 in the Supplement.
The daily 8 h maximum of O3 concentration exceeded 93 ppbv (Chinese
national air quality standard) for 8 of 12 days, and all the
O3-polluted air masses came from the urban region. When the air masses
were from the background region, the daily maximum of O3 was only
approximately 60 ppbv, much lower than that from the urban region. The
NO2 concentration was elevated, with a nocturnal average value over 10 ppbv
during the UAM period. The nocturnal nitrate radical
production rate, P(NO3), was large, with an average of 1.2 ± 0.9 ppbvh-1,
which is comparable with rates previously reported in the NCP
and Hong Kong (Tham et al., 2016; Brown et al., 2016; Z. Wang et al., 2017;
X. F. Wang et al., 2017). The daily peaks of N2O5 were 100–500 pptv
most nights; the maximum of 937 pptv in a 1 min average was observed
near 20:00 CNST on the early night of 2 June, when the P(NO3) was up to 4 ppbvh-1.
The average mixing ratio of N2O5 was 73 ± 90 pptv, which is much higher than recent measurements reported in
northern
China (Tham et al., 2016; X. F. Wang et al., 2017; Z. Wang et al., 2017), but
much lower than that observed in the residual layer of the outflow from the
PRD region, where N2O5 was up to 7.7 ppbv (Wang et al.,
2016). With an elevated O3 mixing ratio in the first half of the night,
the NO lifetime was only several minutes, and the mixing ratio of NO
concentration was observed below the detection limit. During the second half
of the night when the O3 concentration was low, high levels of NO could occasionally be observed, and
N2O5 dropped to zero because of the fast titration by NO, as during
the events that occurred in the second half of the nights of 24, 28, and 30 May.
The PM2.5 mass concentration was moderate during the measurement
period, with an average of 26 ± 21 µgm-3, and the average
Sa was 560 ± 340 µm2cm-3. Elevated ClNO2 was
observed with a daily maximum of over 800 pptv (1 min average) during the UAM period. The maximum of ClNO2 was observed with 2900 pptv in
the morning (05:30 CNST) of 31 May. The observed ClNO2 in Beijing was
comparable with that reported in the NCP (Tham et al., 2016; X. F. Wang et al.,
2017; Z. Wang et al., 2017), but slightly higher than that measured at
coastal (e.g., Osthoff et al., 2008) and inland sites (e.g., Thornton et
al., 2010). Overall, high ClNO2 observed at this site suggested that fast
N2O5 heterogeneous hydrolysis and effective ClNO2 yields
are common in Beijing.
Mean diurnal profiles
The mean diurnal profiles of the measured NO2, O3,
N2O5, and
ClNO2 and the particle chloride content are shown in Fig. 3, as well
as the calculated NO3 based on the thermal equilibrium of NO2,
NO3, and N2O5. Figure 3a shows the average results of the
BAM period, and Fig. 3b shows those of the UAM period. NO2 and
O3 from the UAM, as well as
the mixing ratios of N2O5, NO3 and ClNO2, were much higher than those from the BAM, but the daily
variation tendencies of those species in the two kinds of air masses were
similar. N2O5 began to accumulate in the late afternoon and
increased sharply after sunset. A peak occurred near 20:00 CNST and decreased
below the instrument detection limit at sunrise. The time at which
N2O5 maxima occurred is similar to our previous observation in
urban Beijing (H. C. Wang et al., 2017b). However, the decrease rate of the
observed N2O5 after the peak time was much slower than that in
urban Beijing, where the N2O5 dropped to zero in 2–4 h, which
suggests a relatively slow N2O5 loss rate in suburban Beijing. The
daily average peaks of N2O5 during the BAM period and the UAM
period were 75 and 150 pptv, respectively. The calculated NO3
diurnal profile was quite similar to N2O5, and the daily average
peaks of NO3 during the BAM and UAM periods were approximately 11
and 27 pptv, respectively. The uncertainty of NO3 calculation was
estimated to be 67 % according to Eq. (2), which is dominated by the
uncertainty of NO2 measurement.
Δ[NO3][NO3]=Δ[N2O5][N2O5]2+Δ[NO2][NO2]2+Δ[O3][O3]2+ΔKeqKeq2
The observed ClNO2 concentrations showed a clear increase after
sunset;
ClNO2 reached a maximum before sunrise for the BAM period but around
midnight for the UAM period. The diurnal peak of ClNO2 in the BAM
period was 125 pptv, whereas the diurnal peak of ClNO2 was over 780 pptv
in the UAM period, and 6 times as high as that in the UAM period.
Particulate chloride (Cl-) is a key factor that affects the ClNO2
yield on aerosol surface. Higher particle chloride leads to higher
ClNO2 yield and promotes the N2O5 conversion to ClNO2
(e.g., Finlayson-Pitts et al., 1989; Behnke et al., 1997), whereas the
particle chloride content during the measurement was below 60 pptv and was
much lower than the mixing ratio of ClNO2, suggesting a continuously nighttime
Cl source replenished to support ClNO2 formation. HYSPLIT showed that the air masses mainly came from the continental, not coastal,
regime, suggesting that large amounts of Cl- were not
replenished by NaCl from marine sources, but they possibly replenished by
gas-phase HCl through the acid displacement reaction (Ye et al., 2016).
Cl- was found to be strongly correlated with CO and SO2, likely originating from an anthropogenic source, such as power plants or combustion
sources (Le Breton et al., 2018). According to the mass balance, the gas-phase HCl for supporting the production of ClNO2 is several parts per billion by volume per
night. The required HCl source indicated the ratio HCl / pCl- is about
10–30, which was found to be consistent with the following observation in Beijing.
Although the HCl measurement was not available in this study, note that up
to 10 ppbv of HCl was observed in urban Beijing in September 2016; we
propose that gas-phase HCl was sufficient to support ClNO2
formation.
After sunrise, ClNO2 was photolyzed and decreased with the increasing
photolysis intensity; however, ClNO2 can still survive until noon
with an averaged daily maximum of J(ClNO2) of 1.7 × 10-4 s-1.
Similar to the studies reported in London, Texas, and
Wangdu (Bannan et al., 2015; Faxon et al., 2015; Tham et al., 2016), we
observed sustained elevated ClNO2 events after sunrise on 5 of 12 days.
For example, on the morning of 30 May, ClNO2 increased fast after
sunrise and up to 500 pptv at 08:00 CNST. Such a high ClNO2 increase was
impossible to attribute to the local chemical formation since N2O5
dropped to almost zero and the required N2O5 uptake coefficients
were unrealistically high. A previous study suggested that abundant ClNO2
produced in the residual layer at night and downward transport in the
morning may help to explain this phenomenon (Tham et al., 2016).
The correlation of the mixing ratio of N2O5 and NO2
and the production rate of NO3 on the night of 24 May.
Variation in N2O5 in the background air masses
During the BAM period, the O3 concentration was well in excess of
NO2. In the NO3 and N2O5 formation processes, the
limited NO2 in the high-O3 region indicates that the variation
in
NO2 is more essential to the variation in the N2O5
concentration. As shown in Fig. 4, during the night of 24 May (20:00–04:00 CNST),
the local emission of NO was negligible. The O3 concentration was
larger than 25 ppbv, much higher than NO2 and free of the local NO
emissions. The N2O5 concentration was highly correlated with
NO2 (R2=0.81) and the NO3 production rate (R2=0.60), suggesting the N2O5 concentration was solely a response to the
NO2 concentration in the BAM when enough O3 was
present.
Summary of the field-observed ambient ClNO2 / N2O5.
Location
Region
ClNO2 / N2O5a
References
Beijing, China
Inland
0.7–42.0 (5.4)
This work
Wangdu, China
Inland
0.4–131.3 (29.5)
Tham et al. (2016)
Jinan, China
Marine
25.0–118.0b
X. F. Wang et al. (2017)
Mt. Tai, China
Marine
∼ 4.0
Z. Wang et al. (2017)
Hong Kong, China
Marine
0.1–2.0
Wang et al. (2016)
London, UK
Inland
0.02–2.4 (0.51)
Bannan et al. (2015)
Frankfurt, Germany
Inland
0.2–3.0
Phillips et al. (2012)
Colorado, USA
Inland
0.2–3.0
Thornton et al. (2010)
California, USA
Marine
∼ 0.2–10.0c
Mielke et al. (2013)
a Daily average results. b Power plant plume cases at Mt. Tai
in Shandong, China. c Estimated according to Mielke et al. (2013).
Elevated ClNO2-to-N2O5 ratio
Large day-to-day variabilities in N2O5 and ClNO2 were
observed during the measurement period. Following the work of Osthoff et al. (2008),
Mielke et al. (2013), Phillips et al. (2012), and Bannan et al. (2015),
we used the concentration ratio of ClNO2 to N2O5 to
describe the conversion capacity of N2O5 to ClNO2.
Note that the loss of
N2O5 by dry deposition would drive up the ClNO2 : N2O5. The nighttime peak values and
mean values of ClNO2 : N2O5 were used to calculate the daily
ratios (Table S2); the calculation period is from 19:30 to
05:00 CNST the next day. The average nighttime ratio ranged from 0.7 to 42.0, with a mean of
7.7 and a median of 6.0. ClNO2 formation was effective, with
ClNO2 : N2O5 ratios larger than 1 : 1 throughout the campaign,
except for the night of 26 May, when the ratio was 0.7 : 1. Previous
observations of the ClNO2 : N2O5 ratios are summarized in
Table 2. Compared with the results conducted in similar continental regions
in Europe and America (0.2–3.0), the ratios in this work were
significantly higher and consistent with recent studies in the NCP (Tham
et al., 2016; X. F. Wang et al., 2017; Z. Wang et al., 2017), which suggests
that high ClNO2 : N2O5 ratios were ubiquitous in the NCP and
implies that ClNO2 yield via N2O5 uptake is efficient.
Summary of the average γ×f values derived in the
field observations.
Location
Region
γ×f
References
Beijing, China
Suburban
0.019 ± 0.009
This work
Frankfurt, Germany
Suburban
0.014
Phillips et al. (2016)
Mt. Tai, China
Suburban
0.016
Z. Wang et al. (2017)
Jinan, China
Urban
< 0.008
X. F. Wang et al. (2017)
California, USA
Urban
0.008
Mielke et al. (2013)
Discussion
Determination of N2O5 uptake coefficients
A composite term, γ×f, was used to evaluate the production
of ClNO2 from N2O5 heterogeneous hydrolysis (Mielke et al.,
2013). γ×f was estimated by fitting the observed ClNO2
in a time period when the nighttime concentrations of ClNO2 increased
continuously. The increased ClNO2 was assumed to be solely
from the N2O5 uptake. The fitting was optimized by changing the
input of γ×f associated with the measured N2O5
and Sa, until the ClNO2 increase was well reproduced (Eq. 3).
[ClNO2]t=[ClNO2]t0+(γ×f)⋅∫t0tC⋅Sa4[N2O5]dt
Here t0 and t denote the start time and end time, respectively; the
calculation time duration was normally several hours.
[ClNO2](t0) is the observed concentration at t0 and set as the
fitting offset. Note that the transport leads to the bias of the N2O5
uptake coefficient and ClNO2 yield. But the small variation in the
mixing ratio of CO (< 5 %) during each analysis time period
suggested the transport process is not important to the increasing
ClNO2. The derived γ×f was found to be constant with
small uncertainties for optimization (see Table S3). The γ×f had moderate variability and ranged from 0.008 to 0.035 with an
average of 0.019 ± 0.009. Table 3 summarizes the γ×f values derived in the previous field observations. The value in suburban
Germany was between 0.001 and 0.09, with an average of 0.014 (Phillips et
al., 2016), and the average value in Mt. Tai, China, was approximately 0.016
(Z. Wang et al., 2017). The average γ×f in this study was
comparable with that of the two suburban sites, whereas at an urban site of
Jinan, China (X. F. Wang et al., 2017), the value was lower than 0.008 and
comparable with that in the CalNex-LA campaign. The three sets of γ×f values from suburban regions were about twice as large as those
in urban regions, which implies that the ClNO2 formation efficiency in
the aged air masses in suburban regions was higher than in the
urban region. The difference of the overall yield between the two regions
may be caused by particle properties or other factors (Riemer et al., 2009;
Gaston et al., 2014; Gržinić et al., 2015; Bertram and Thornton, 2009).
According to reaction R4, soluble nitrate and ClNO2 were formed by
N2O5 heterogeneous uptake, with yields of 2-f and f, respectively.
Following the recent work of Phillips et al. (2016), we used the observed
pNO3- and ClNO2 formation rates to derive individual
γ and f. The calculations assumed that the relevant properties of the
air mass are conserved and that the losses of produced species are
negligible; additionally, the N2O5 uptake coefficients and the
ClNO2 yield are independent of particle size. The nights
characterized by the following two features were chosen for further
analysis: (1) significant correlations between pNO3- and
ClNO2 were present (R2>0.5), which suggested that,
to a good approximation, both ClNO2 and pNO3- are produced
only by N2O5 heterogeneous uptake. The reason for excluding other
nights with low correction (R2<0.2) was that ClNO2 and
pNO3- may be affected by the effective transport or other
production pathways, and these contributions cannot be well quantified.
Therefore the selection of a high correction of ClNO2 with
pNO3- may lead to a bias as the contribution from other formation
pathways and the transport were neglected. (2) During an increasing period
of pNO3-, an equivalent or faster increase in ammonium
to pNO3- was also observed, which means enough gas-phase ammonia
was repartitioned to form ammonium nitrate and suppress the release of
HNO3. The ammonia-rich conditions (22 ± 9 ppbv on average) in
Beijing demonstrated that the degassing of HNO3 at night can be
effectively buffered by the high concentrations of ammonia presented in the
NCP (Liu et al., 2017). Both gas–particle repartitioning of HNO3
and
nighttime-produced HNO3 will result in the overestimation of γ
and the underestimation of f. The daytime-produced HNO3 will soon be in
a new equilibrium rapidly on the timescale of total nitrate chemical
production, and the nighttime formation of HNO3 is normally not
important; thus the nocturnal HNO3 uptake impact is negligible. During
this campaign, five nights were eligible for the following analysis. The observational data of N2O5, ClNO2, pNO3-, and
Sa were averaged to 5 min for the following analysis. The formations of pNO3- and
ClNO2 were integrated to reproduce the increasing pNO3- and
ClNO2 by inputting an initial γ and f. The offset of pNO3-
and ClNO2 is the measured pNO3- and ClNO2 concentration
at the start time. γ and f were optimized based on the
Levenberg–Marquardt algorithm until good agreement between the observed and
predicted concentrations of pNO3- and ClNO2 was obtained
(Phillips et al., 2016). Figure 5 depicts an example of the fitting results
on 28 May. The predicted N2O5 uptake coefficient and ClNO2
yield were 0.017 and 1.0, respectively. The uncertainty on each individual
fitting is varied from 55 to 100 % due to the variability in and
measurement uncertainties of pNO3- and ClNO2. Five
sets of values of γ and f obtained are listed in Table 4.
N2O5 uptake coefficients ranged from 0.012 to 0.055, with an
average of 0.034 ± 0.018, and the ClNO2 yield ranged from 0.50 to
unity, with an average of 0.73 ± 0.25. The errors from each derivation
were 55 % and came from the field measurements of Sa, N2O5,
pNO3-, and ClNO2.
List of the N2O5 uptake coefficients and the yield of
ClNO2 in this campaign.
Start time
End time
γ
f
25 May, 00:00
25 May, 05:00
0.047 ± 0.023
0.60 ± 0.30
25 May, 18:30
25 May, 23:00
0.012 ± 0.006
1.0 ± 0.50
27 May, 19:00
27 May, 20:40
0.040 ± 0.032
0.50 ± 0.40
28 May, 19:00
28 May, 23:00
0.017 ± 0.009
1.0 ± 0.50
30 May, 21:00
31 May, 00:00
0.055 ± 0.030
0.55 ± 0.30
The best fit of γ and f to reproduce the observed ClNO2
and pNO3- with an offset on 28 May. The black lines are the
predicted results of the integrated NO3- and ClNO2 by using
the observed Sa and N2O5.
The average γ value was consistent with the results determined by
the same method at a rural site in Germany (Phillips et al., 2016) but was
higher than those in the UK and North America where they used other
derivation methods, including the steady-state lifetime method (Morgan et
al., 2015; Brown et al., 2006, 2009), the iterated box model (Wagner et al.,
2013), and direct measurement based on an aerosol flow reactor (Bertram et
al., 2009; Riedel et al., 2012). The steady-state lifetime method is very
sensitive to NO2 concentration, and since the NO2 measurement
suffered with ambient NOy interference, we did not apply the steady-state
lifetime method in this study (Brown et al., 2003). Nonetheless, the derived
γ in Beijing showed good agreement with the recent results derived
with the steady-state method in Jinan and Mt. Tai (X. F. Wang et al., 2017; Z. Wang et al., 2017).
The consistency eliminates the discrepancy possibly
brought about by the differences in analysis methods. Therefore, we suggest that
fast N2O5 uptake was a ubiquitous feature that existed in the
NCP. In this study, sulfate is the dominant component of PM1.0,
accounting for more than 30 % of its mass concentration, which may be the
reason for the elevated N2O5 uptake coefficient present in Beijing,
like the results for high sulfate air mass over Ohio and western Pennsylvania
(Brown et al., 2006). Previous studies have shown that the N2O5
uptake coefficient strongly depends on the liquid water content,
pNO3-, and organic mass. Liquid water content promotes
N2O5 uptake, whereas pNO3- and organic mass inhibit
N2O5 uptake (e.g., Thornton et al., 2003; Wahner et al., 1998;
Bertram and Thornton, 2009). Because of the limited data set of
N2O5 uptake coefficients in this work, the function dependence
studies on the determined N2O5 uptake coefficients with the
parameters mentioned above were not convincing. More valid data are needed
in the further studies of the N2O5 uptake mechanism. With respect
to f, the values are comparable to those observed in Germany (Phillips et
al., 2016) and are similar to those estimated in the power plant plume in Mt. Tai with high chloride content (Z. Wang et al., 2017).
N2O5 lifetime and reactivity
The lifetime of N2O5 was estimated using the steady-state method,
assuming that the production and loss of N2O5 was in balance after
a period following sunset. Equation (4) for the steady-state approximation has been
frequently applied in analyzing the fate of N2O5 (Platt et al.,
1980; Allan et al., 1999; Brown et al., 2003).
τss(N2O5)=1Lss(N2O5)=[N2O5]kNO2+O3[NO2][O3]
Here τss(N2O5) denotes the steady-state lifetime of N2O5 and
Lss(N2O5) denotes the loss term of N2O5
corresponding to the steady-state lifetime. A numerical model was used to
check the validity of the steady-state approximation (Brown et al., 2003);
details are given in Fig. S3. The results show that the steady state can
generally be achieved within 30 min. In this study, the steady-state
lifetime was only calculated from 20:00 to the next day at 04:00 CNST. The time
periods with a NO concentration larger than 0.06 ppbv (instrument LOD) were
excluded as the steady state is easily disturbed. The overall N2O5
loss rate (k(N2O5)) can be calculated by accumulating each
individual loss term in Eq. (5), including the N2O5 heterogeneous
hydrolysis and the reaction of NO3 with VOCs.
kN2O5=∑kNO3+VOCsi⋅[VOCsi]keq⋅NO2+C⋅Sa⋅γ4
The NO3 heterogeneous uptake and the loss of N2O5 via
gas-phase reactions were assumed to be negligible (Brown and Stutz, 2012).
kNO3+VOCsi denotes the reaction rate constants of the
reaction of NO3 + VOCsi. Isoprene and monoterpene were used in
this calculation.
The dependence of N2O5 lifetime on aerosol
surface area. Data were selected from 20:00 to 04:00 CNST and are shown as
medians, 25–75th percentile ranges, and 10–90th percentile
ranges, as shown in the legend.
Time series of the individual N2O5 loss terms and the
loss rate constant of N2O5 in steady state
(Lss(N2O5)).
The N2O5 loss rate coefficient by heterogeneous hydrolysis was
calculated by using an average γ of 0.034. The time series
of the steady-state lifetime of N2O5 is shown in Fig. S4. The
N2O5 steady-state lifetime ranged from < 5 to 1260 s,
with an average of 270 ± 240 s, and large variability was shown during
the campaign. The N2O5 lifetimes during the BAM period were higher
than those during the UAM period, which is predictable since the clean air
mass has lower N2O5 reactivity because of much lower aerosol
loading. Two extremely short N2O5 lifetime cases were captured on
the nights of 30 May and 3 June, with peak values below 200 s throughout
those nights. Figure 6 shows that the N2O5 lifetime had a very
clear negative dependence on the ambient Sa when larger than 300 µm2cm-3, which indicates that the N2O5 heterogeneous
uptake plays an important role in the regulation of N2O5 lifetime.
The study conducted in the residual layer of Hong Kong showed a similar
tendency despite the overall N2O5 lifetime being shorter at this
site (Brown et al., 2016). Additionally, a negative dependence of
N2O5 lifetime on RH was reported in Hong Kong but was not observed
in this study (Fig. S5).
Figure 7 shows the time series of the overall N2O5 loss rate
constant as well as the N2O5 steady-state loss rate constant.
The overall N2O5 loss rate constant was calculated from the
individual terms (Eq. 3). The uncertainties of the N2O5 steady-state loss rate constant and the overall k(N2O5) are estimated to
be 67 and 95 %, respectively (Eqs. 6 and 7). The largest error
sources were from the corrected NO2 measurements.
ΔLss(N2O5)Lss(N2O5)=Δ[N2O5][N2O5]2+Δ[NO2][NO2]2+Δ[O3][O3]2+ΔKeqKeq2Δk(N2O5)k(N2O5)=Δ[N2O5][N2O5]2+Δ[Sa][Sa]2+Δ[γ][γ]2+Δ[NO2][NO2]2+Δ[O3][O3]2+Δ[VOCs][VOCs]2+ΔKeqKeq2
On the night of 29 May, the steady-state loss rate constant was much
lower than the overall k(N2O5); on the nights of 28 May and 3 June,
the Lss(N2O5) values calculated with the steady-state method were
much higher than the overall k(N2O5), but these discrepancies were
in the range of the uncertainties. The steady-state loss rate constant in
the case of 30 May was approximately 10 times larger than the overall loss
rate constant, and this difference was outside of the range of uncertainty.
The reason for the larger difference on this night is not understood from
the available measurements. In general, the overall N2O5 loss rate
constant and the steady-state N2O5 loss rate constant were
comparable, taking into consideration the uncertainties. The average
N2O5 loss rate constant contributed by the N2O5
heterogeneous hydrolysis was 8.1×10-4 s-1. The average
NO3 loss rate constant by the reaction of NO3 with VOCs was 0.015 ± 0.007 s-1,
which is comparable with the previous results in
suburban Beijing in 2006 (H. C. Wang et al., 2017b), in which the
contribution to the N2O5 reactivity was 1.63×10-3 ± 0.65×10-3 s-1 on average. Compared with
N2O5 loss via direct heterogeneous hydrolysis, the indirect loss
via NO3 + VOCs was dominant, accounting for approximately 67 %.
Because only a subset of the suite of organic species at the site was
measured, the calculated loss rate constant via NO3 + VOCs represents a
lower limit. Therefore, the N2O5 loss via NO3 + VOCs may
occupy a larger proportion. The overall loss rate constant from
NO3 + VOCs and N2O5 uptake was 2.44×10-3 ± 1.5×10-3 s-1
on average, which was reasonably
lower than the steady-state N2O5 loss rate constant of
3.61×10-3 ± 2.80×10-3 s-1 on
average. The gap may be explained by the unmeasured reactive VOCs or the
unaccounted for NO that was near the instrumental limit of detection.
NO3-induced nocturnal oxidation of VOCs
Recent studies have suggested that the fate of BVOCs after sunset is
dominated by NOx or O3, with variation in the ratio of NOx to
BVOCs and that the nighttime oxidation is located in the transition region
between NOx domination and O3 domination in the United States
(Edwards et al., 2017). During this campaign, the nocturnal average
concentrations of isoprene and monoterpene were 156 ± 88 and 86 ± 42 pptv,
respectively. We used isoprene and monoterpene to represent
a lower limit mixing ratio of total BVOCs; the average ratio of
NOx / BVOCs was larger than 10 and exhibited small variation during the
BAM and UAM periods. The value was much higher than the critical value
(NOx / BVOC = 0.5) of the transition regime proposed by Edwards et al. (2017),
which suggests that the oxidation of BVOCs in Beijing was
NOx dominated and the nighttime fate of BVOCs was controlled by
NO3. Since the reaction of NO3 with BVOCs has a high mass yield,
the nocturnal ON production may be important in the high NOx / BVOC
region.
The first-order loss rate of VOCs initialized by oxidants, k(VOCsi), is
defined as VOC reactivity and expressed as Eq. (8). Here, we only consider
the reaction of VOCs with O3 and NO3. kO3+VOCsi
denotes the reaction rate constants of VOCsi with O3.
k(VOCsi)=kNO3+VOCsi⋅NO3+kO3+VOCsi⋅O3
During this campaign, VOC reactivity could be determined with the measured
O3 and calculated NO3. Figure 8 depicts four kinds of VOC
reactivity distribution during nighttime, including the isoprene (ISO),
monoterpene (MNT), double bond at the end or terminal position of the
molecule (OLT), and alkenes with the double bond elsewhere in the molecule
(OLI). The reaction rates were cited from the Regional Atmospheric Chemistry
Mechanism version 2 (RACM2; Goliff et al., 2013). Previous measurement
indicated the main detectable monoterpenes were α-pinene and β-pinene in summer in Beijing (Ying Liu, personal communication, 2018). Here we
assumed α-pinene and β-pinene occupy half and half in the
monoterpene with an uncertainty of 50 %. The rate coefficients of
α-pinene and β-pinene with NO3 were referred to in Atkinson
and Arey (2003). The uncertainty of the calculated mixing ratio of NO3 is
67 %, and the overall uncertainty of monoterpene reactivity was calculated
to be 85 % with Gaussian propagation. The uncertainties of other kinds of
VOCs was calculated to be 75 % by assuming the uncertainty of rate
coefficient was 30 %. The VOC reactivity was dominated by NO3
oxidation and contributed up to 90 % in total; less than 10 % of VOCs were
oxidized by O3 during the nighttime. Even though the NO3 concentration is in
the lower range, NO3 is still responsible for more than 70 % nocturnal
BVOC oxidation, and the results further confirmed that the oxidation of BVOCs
is controlled by NO3 rather than O3 in summer in Beijing.
The nighttime VOC reactivity of NO3 and O3 (defined as
the first-order loss rate of VOCs initialized by oxidants, including NO3
and O3); the VOCs are classified as isoprene (ISO), monoterpene (MNT), terminal alkenes (OLT), and internal alkenes (OLI). The data were
selected from 20:00 to the next day at 04:00 CNST.
The nighttime production rate of organic and inorganic nitrates;
the inorganic nitrates were calculated from N2O5 heterogeneous
hydrolysis, and ONs were calculated with the NO3 reacted with isoprene
and monoterpene.
For calculating nocturnal ON production from NO3 oxidation of isoprene
and monoterpene, as well as inorganic nitrate production via N2O5
heterogeneous uptake over the same period, the ClNO2 yield was set to
the determined average value of 0.55. The organic nitrate yield of the
reaction of NO3 with isoprene was set to 0.7, from Rollins et al. (2009). The
yield from the reaction of NO3 with monoterpene was
represented by NO3 + α-pinene and was set to 0.16,
following Spittler et al. (2006). As α-pinene and β-pinene have very different ON yields, the yield set in the study was an
upper limit for α-pinene-initialized ON, but has a relatively low yield for
the β-pinene-initialized ON (e.g., Hallquist et al., 1999). Although
the yield from the NO3 oxidation of isoprene is much higher than that
of monoterpene, the total ON production was dominated by the oxidation of
NO3 with monoterpene because the reaction of NO3 with monoterpene
is much faster than that with isoprene. Because of the lack of measurement
of alkenes and other VOCs that can react with NO3 and form ON, the
calculated nighttime ON production rate analyzed here served as a lower
estimation.
Figure 9 depicts the mean diurnal profiles of the nocturnal formation rates
of inorganic nitrates and ON. The average production rate of ON was up to
0.10 ± 0.07 ppbvh-1, which was higher than that predicted at a
suburban site in Beijing in 2006, with an average value of 0.06 ppbvh-1 (H. C. Wang et al., 2017c).
In the high NOx / BVOC air masses,
the inorganic nitrate formation was proposed to increase with the increase
in sunset NOx / BVOC (Edwards et al., 2017). The formation rate of
inorganic nitrate via N2O5 uptake was significant, with an average
of 0.43 ± 0.12 ppbvh-1, and was much larger than the ON
formation. NOx was mainly removed as the inorganic nitrate format by
nocturnal NO3–N2O5 chemistry in Beijing. Overall, the
NO3–N2O5 chemistry led to significant NOx removal, with
0.54 ppbvh-1 accounted for by the organic and inorganic nitrates, and
the integral NOx removal was approximately 5 ppbv per night. Since
ONs
are important precursors of the SOAs,
NO3 oxidation was very important from the perspective of organic
aerosol formation and regional particulate matter (e.g., Ng et al., 2008).
Conclusion
We reported an intensive field study of NO3–N2O5 chemistry at
a downwind suburban site in Beijing during the summer of 2016. High levels
of ClNO2 and N2O5 were observed, with maxima of 2.9 and
937 pptv (1 min), respectively. The N2O5 uptake coefficient was
estimated to be in the range of 0.010–0.055, with an average value of 0.034 ± 0.018,
and the corresponding ClNO2 yield was derived to be in
the range of 0.5–1.0, with an average value of 0.73 ± 0.25. The
elevated ClNO2 levels and ClNO2 / N2O5 ratios are
comparable with those in chloride-rich regions in the NCP. The results
highlight fast N2O5 heterogeneous hydrolysis and efficient
ClNO2 formation in the outflow of urban Beijing.
Since the NO3–N2O5 chemical equilibrium favors NO3 in
summer with high temperature, the elevated NO3 dominated the nocturnal
degradation of BVOCs and could lead to efficient ON formation. Because the
air masses in Beijing featured high NOx / BVOC ratios (> 10),
our results suggest that the nocturnal NO3 oxidation of BVOCs was
NOx dominated. Because of the extremely high NOx emissions, the
formation of ON may not be sensitive to the reduction of NOx but rather
to the change of unsaturated VOCs (e.g., BVOCs), which is similar to the
daytime photochemical O3 pollution (e.g., Lu et al., 2010) diagnosed
for this area. This suggests that control of the unsaturated VOCs would
moderate O3 pollution and ON particulate matter in parallel.
Moreover, reduction of NOx would also be helpful in reducing the
pNO3- formation via N2O5 heterogeneous hydrolysis under
such high NOx / BVOC ratios (Edwards et al., 2017).