A comprehensive field campaign, with measurements of HONO and related
parameters, was conducted in summer 2018 at the foot (150 m a.s.l.) and the
summit (1534 m a.s.l.) of Mt. Tai (Shandong province, China). At the summit
station, high HONO mixing ratios were observed (mean ± 1σ: 133 ± 106 pptv, maximum: 880 pptv), with a diurnal noontime peak (mean ± 1σ: 133 ± 72 pptv at 12:30 local time). Constraints on
the kinetics of aerosol-derived HONO sources (NO2 uptake on the aerosol
surface and particulate nitrate photolysis) were performed and discussed,
which enables a better understanding of the interaction of HONO and
aerosols, especially in the polluted North China Plain. Various
evidence of air mass transport from the ground to the summit level was
provided. Furthermore, daytime HONO formation from different paths and its
role in radical production were quantified and discussed.
We found that the homogeneous reaction NO + OH could only explain 8.0 %
of the daytime HONO formation, resulting in strong unknown sources
(Pun). Campaigned-averaged Pun was about 290 ± 280 pptv h-1, with a maximum of about 1800 pptv h-1. Aerosol-derived HONO
formation mechanisms were not the major sources of Pun at the summit
station. Their contributions to daytime HONO formation varied from
negligible to moderate (similar to NO + OH), depending on the
chemical kinetic parameters used. Coupled with sensitivity tests on the
kinetic parameters used, the NO2 uptake on the aerosol surface and
particulate nitrate photolysis contributed 1.5 %–19 % and 0.6 %–9.6 %
of the observed Pun, respectively. Based on synchronous measurements at
the foot and the summit station, an amount of field evidence was proposed to
support the finding that the remaining majority (70 %–98 %) of Pun was dominated
by the rapid vertical transport from the ground to the summit level and
heterogeneous formation on the mountain surfaces during transport.
HONO photolysis at the summit level initialized daytime photochemistry and
still represented an essential OH source in the daytime, with a contribution
of about one-quarter of O3. We provided evidence that ground-derived
HONO played a significant role in the oxidizing capacity of the upper
boundary layer through the enhanced vertical air mass exchange driven by
mountain winds. The follow-up impacts should be considered in regional
chemistry transport models.
Introduction
In the past 2 decades, atmospheric nitrous acid (HONO) has attracted
numerous laboratory experiments and field campaigns because of its
significant contribution to the production of hydroxyl radicals (OH) and the
incomplete understanding of its sources
(Kleffmann, 2007). Besides the homogeneous
reaction of NO with OH, various HONO formation pathways were proposed,
including (a) emissions from combustion processes, e.g., vehicle exhaust,
domestic combustion and biomass burning
(Klosterköther
et al., 2021; Kramer et al., 2020; Kurtenbach et al., 2001; Liu et al.,
2017; Peng et al., 2020; Theys et al., 2020); (b) dark and photosensitized
heterogeneous reactions of NO2 on surfaces, such as soot
(Ammann et
al., 1998; Monge et al., 2010), organic compounds
(George
et al., 2005; Han et al., 2017; Stemmler et al., 2006, 2007), acids
(Kleffmann et al., 1998), urban grime
(J. Liu et al.,
2019), MgO (Ma et al., 2017), mineral dust
(Ndour et al., 2008), and vegetation leaves
(Marion et al., 2021); (c) photolytic reactions of
total nitrate (particulate nitrate and adsorbed nitric acid)
(Bao
et al., 2018; Laufs and Kleffmann, 2016; Ye et al., 2016; Zhou et al., 2003,
2011) and ortho-nitrophenols (Bejan et al., 2006); and
(d) emissions from soil
(Donaldson
et al., 2014; Oswald et al., 2013; Su et al., 2011; Xue et al., 2019a).
Though many potential HONO sources have been identified in the past, there
is still a significant gap between model results and observations
(Fu
et al., 2019; Liu et al., 2017; Xue et al., 2020; Zhang et al., 2019a,
b). One of the critical puzzles is the quantity of HONO formation from
the aerosol-derived sources, particularly NO2 uptake on aerosol
surfaces and aerosol nitrate photolysis in high-aerosol regions such as the
North China Plain (NCP).
The NO2 uptake on aerosol surfaces was proposed to be much less
important than that on ground surfaces in previous studies because of the
low S/V (surface-to-volume ratio) of particles compared to ground surfaces
and the similar reaction kinetic parameters on the same types of surfaces
(Nie
et al., 2015; Stemmler et al., 2007). However, the contribution of NO2
uptake on aerosol surfaces to HONO formation in the extremely polluted
region is not well constrained. For example, previous studies using box
models or regional transport chemistry models found that NO2 uptake on
aerosol surfaces led to a negligible impact on daytime HONO formation in
the polluted NCP
(Y. Liu
et al., 2019; Xue et al., 2020; Zhang et al., 2019a, b). Nevertheless,
a recent chamber study (Ge et al., 2019) found a high dark
NO2 uptake coefficient (2.0 × 10-5 to 1.7 × 10-4) on NaCl particles under high RH (90 %), NH3 (50–2000 ppbv), and SO2 (600 ppbv) conditions. First, such severe pollution
rarely occurred. Second, if such a high NO2 coefficient on the aerosol
surface was applied in nighttime HONO budget analysis, the dominant role of
NO2 uptake on the ground surface in nighttime HONO formation, which
was already generally accepted, might be challenged
(Kleffmann,
2007; Kurtenbach et al., 2001; Stutz et al., 2002; Xue et al., 2020).
In addition, recent nocturnal vertical measurements of HONO in Beijing found
that both ground-based and aerosol-derived sources may play important roles in
HONO formation during the clean period and haze period, respectively
(Meng et al., 2020). Therefore, the contribution of NO2
uptake on the aerosol surface to HONO formation still needs more field
constraints.
The photolysis of particulate nitrate (pNO3) was found to be an
important HONO source in low-NOx areas such as forest canopy and the marine
boundary layer. High enhancement factors (EFs =J(pNO3)/J(HNO3)),
within the range of tens to thousands, were proposed in forest areas, the
marine boundary layer, and polluted areas like the NCP
(Bao
et al., 2020; Ye et al., 2016, 2017; Zhou et al., 2007, 2011). However,
model studies with field constraints
(Romer
et al., 2018; Xue et al., 2020) found that the EF was moderate (7–30) rather
than tens to thousands obtained in laboratory studies
(Bao
et al., 2020; Ye et al., 2016, 2017; Zhou et al., 2007). Moreover, a recent
laboratory flow tube study (Wang et al., 2021) revealed
that the EF was lower than 1 in the aqueous phase. Another flow tube study
(Laufs and Kleffmann, 2016) also reported a slow HONO formation
from secondary heterogeneous reactions of NO2 produced during HNO3
photolysis. In addition, a recent chamber study (Shi
et al., 2021) found that the EF values of airborne nitrate were lower than
10 (generally around 1), which also indicates an insignificant contribution
of nitrate photolysis to HONO formation. Furthermore, when considering the
large variation of EF values (from digits to thousands) in the model, model
performance on HONO simulations could be improved but was accompanied by large
uncertainties (Fu
et al., 2019; Y. Liu et al., 2019b; Zhang et al., 2021). Therefore, HONO
formation from nitrate photolysis also needs more field constraints.
Moreover, the role of HONO photolysis in the oxidizing capacity of the upper
boundary layer remains unclear. As there is a significant gradient in
HONO distribution, HONO photolysis was found to be much less important
compared to O3 photolysis in the upper boundary layer compared to the
lower boundary layer
(Ye et
al., 2018; Zhang et al., 2009). However, in mountainous regions, mountain
winds, including mountain breeze (downslope) and valley breeze (upslope) can
accelerate the air mass exchange between the mountain summit and the ground
levels, which may affect HONO levels and the atmospheric oxidizing capacity
at the summit level (Jiang
et al., 2020; Schmid et al., 2020; Ye et al., 1987).
Atmospheric measurements at the foot (∼ 150 m a.s.l.)
and the summit (∼ 1534 m a.s.l.) of Mt. Tai were conducted in
summer 2018 and presented in this study. Comprehensive measurements allow us
to understand more about (1) the transport of ground-formed HONO and its role
in the upper boundary layer, (2) HONO formation from the aerosol-derived
sources as the ground-derived sources might be less effective compared to
measurements near to ground surface, and (3) the oxidizing capacity of the upper
boundary layer and its contributors.
ExperimentalSite description
HONO was alternately measured at two locations: the foot and the summit of
Mt. Tai (Figs. 1 and S1). The foot station is
inside the Shandong College of Electric Power, a typical urban site
(36.18∘ N, 117.11∘ E). HONO, volatile organic compounds (VOCs), oxygenated VOCs (OVOCs), CO, O3,
SO2, NOx, PM2.5, PM10, J(NO2), and meteorological
parameters were continuously measured at this station. Details about the
foot station and the instruments used can be found in the companion study
(Xue et al., 2022). The summit station (36.23∘ N,
117.11∘ E) is located inside a meteorological observatory at the
eastern part of the summit of Mt. Tai, with an altitude of about 1534 m a.s.l. It is in the north part of Tai'an (altitude: ∼ 150 m, population: ∼ 5.6 million), and about 60 km south of Jinan (the capital city of Shandong province, altitude: ∼ 20 m,
population: ∼ 8.7 million).
Since Mt. Tai is a famous tourist place, most of the tourist activities on
the summit happen around the Southern Heavenly Gate, the Bixia Temple, and
the Jade Emperor Peak. The most crowded period is around sunrise, when
visitors come for the view of sunrise. The Southern Heavenly Gate is about 1 km west of and about 100 m lower than our station. There are several small
restaurants nearby, but they do not cause significant emissions as they only
use electricity for their energy supply. The Bixia Temple is about 200 m west
to and about 50 m lower than our station, and small anthropogenic emissions
may be produced here because of the incense burning, but the impact on our
measurements is expected to be negligible as a result of the fast dilution
process at the summit level. The Jade Emperor Peak is about 200 m northwest
of and has a similar altitude to our station. Visitors generally stay there
for a short time and do not conduct activities that may produce significant
emissions. A detailed discussion about the influence of anthropogenic
emissions at the summit level on our measurements is presented in Sect. 3.2.1.
Locations of Mt. Tai, the summit station, and the ground station.
(a) Locations of Mt. Tai and nearby cities (Tai'an and Jinan) colored by
altitude; the black arrow represents the dominated wind direction. (b) Contour map of Mt. Tai; the black and yellow stars represent the
locations of the summit and the ground stations, respectively. (c) A view
of the station from the southwest. Map data were taken from the National
Catalogue Service for Geographic Information (https://www.webmap.cn, last access: 7 March 2022). Photo copyright: Chaoyang Xue.
Instrumentation
During the campaign, HONO was continuously measured by the LOPAP instrument
(LOng Path Absorption Photometer, Model-03, QUMA GmbH, Germany) with a
detection limit of 1.5 pptv for 5 min on average
(Heland
et al., 2001; Kleffmann et al., 2006). The performance of LOPAP was well
assessed and recorded in different environmental conditions
(Heland et al., 2001), including
low-NOx and high-altitude sites (Kleffmann
and Wiesen, 2008). In addition, this LOPAP has been successfully used in our
previous studies
(Xue
et al., 2019b, 2020). The LOPAP instrument was installed at the foot station
from 29 May to 8 July 2017 and then transported to the summit
station with successful measurements from 9 to 31 July 2017.
At the summit station, a temperature-controlled measurement container was
used to house all the instruments. The external sampling unit of LOPAP was
installed on the top of the container, about 2.5 m above the ground surface.
Zero air (ultrapure N2) measurements were conducted two or three times per
day. Liquid calibration with diluted standard nitrite solution
(Sigma-Aldrich) was conducted every week. Both zero air measurements and
liquid calibration were conducted after changing any solution, cleaning the
instrument, or replacing any component of the instrument (the air pump was
broken on 21 July and replaced by a new one on 25 July). The
precision of the instrument determined from 2σ noise of the
calibration was 1 %. An accuracy of 7 % was determined by error
propagation including all known uncertainties, i.e., the concentration of
the calibration standard (±3 %–4 %) and the liquid (±1 %)
and gas flow (±2 %) rates. Known artificial HONO formation on inlet
surfaces (e.g., Zhou et al., 2002) was minimized by
using the external sampling unit, with only a 3 cm sunlight-shielded glass
inlet to the ambient atmosphere. Other interferences were considered of
minor importance, as they were corrected for by the two-channel concept of
the instrument. In addition, excellent agreement between LOPAP and differential optical absorption spectroscopy (DOAS)
techniques was observed under complex conditions in a smog chamber and in
the ambient atmosphere
(Kleffmann et al., 2006).
NO2 was measured by a Model T500U CAPS NO2 analyzer (Teledyne API,
USA) that utilizes a patented Cavity Attenuated Phase Shift (CAPS) technique
to measure NO2 in the air directly. NO and NOy were measured by
an API T200U NOy analyzer (Teledyne API, USA) based on the
chemiluminescence principle coupled with a remote NOy converter via
umbilical cable to allow for measurements with a lower detectable limit of 50 pptv.
PM2.5 was measured by a SHARP 5030 monitor (Thermo Scientific, USA). CO
and SO2 were measured by a T300U-CO monitor (Teledyne API, USA) and a
Model 43C SO2 monitor (Thermo Scientific, USA), respectively.
J(NO2) was measured by a 4-πJ(NO2) filter radiometer (Metcon
GmbH, Germany). Other J values used in this study, including J(HONO),
J(O(1D)), and J(HNO3), are calculated by the trigonometric solar zenith angle (SZA)
function (MCM default photolysis frequency calculation; see the companion
paper and Jenkin et al., 1997) and
scaled by the measured J(NO2). For instance, J(HONO) =J(HONO)model×J(NO2)measured/J(NO2)model.
Water-soluble ions, including particulate nitrate (pNO3) of PM2.5,
were collected by filter method and analyzed by an ion chromatograph
(Liu et al., 2020) every 2 h late June and early July, but
it suffered a sampling problem after 12 July. Aerosol size (13.6–763.5 nm) distribution was measured by a scanning mobility particle sizer
(SMPS; Model 3938, TSI Inc., USA) equipped with a differential mobility
analyzer (DMA; Model 3082, TSI Inc., USA) and a condensation particle
counter (CPC; Model 3775, TSI Inc., USA). Meteorological parameters
(temperature, relative humidity, wind speed, and wind direction) were measured
by instruments from the Shandong Taishan Meteorological Station
simultaneously, and details can be found in previous studies at this station
(Jiang et al., 2020). In this study, 10 min averaged data
were used for the following analysis. Details about the instrumentation at
the foot station can be found in the companion ACP paper. Measurements at
the foot station ended on 16 July. To compare pollutants between the
foot and the summit levels during the same period (Sect. 3.2.2),
measurements (only hourly CO, NO2, PM2.5, PM10, O3, and
SO2 were available) from the monitoring station (∼ 200 m
east to the foot station) were used.
Results and discussionOverview of the observations
Figure 2 shows the meteorological parameters
measured at the summit of Mt. Tai during the campaign. The air temperature
(T in ∘ C) was slightly lower (∼ 17 ∘C) in the first 2 d compared to the period after
10 July (∼ 20 ∘C). As clouds were
frequently formed at the summit (Li et al., 2020), the
observed relative humidity (RH) commonly reached 100 %, with a mean of
96 %. Based on the wind measurements, air mass at the summit mainly came
from the south (direction of Tai'an), with a mean wind speed (WS) of
5.1 m s-1. In particular, during the period of 23 to 26 July, high wind speed (1 min max: 19.5 m s-1, 10 min max: 18.5 m s-1) was observed, accompanied by a relatively low temperature, low
pressure (p), low radiation (J(NO2)), and high RH.
Meteorological parameters measured at the summit of Mt. Tai during
the campaign.
Figure 3 illustrates the time series of HONO and
related pollutants measured at the summit station. Several pollution events
were observed. For example, the measured daytime PM2.5 was generally
larger than 20 µgm-3, and high SO2 mixing ratios
(> 1 ppbv) were observed during the daytime on some days (i.e.,
from 14 to 26 July). NO mixing ratios were generally lower
than 0.5 ppbv due to significant suppression by high O3 levels of
usually higher than 50 ppbv. NO2 was generally lower than 2 ppbv with
several events, during which NO2 was relatively high. In addition, the
measured HONO mixing ratio varied from 1.1 pptv (close to the detection
limit) to 880 pptv, with a mean of 133 pptv and a median of 101 pptv,
respectively (Table 1). For the same sampling site
at the summit of Mt. Tai, as listed in Table 2, the
observed mean HONO mixing ratio in summer is similar to those observed in
winter (150 pptv, December 2017) and spring (130 pptv, March–April 2018)
reported by Jiang et al. (2020), but the variation of
HONO mixing ratios in summer was within a much narrower range (1–880 pptv) than in winter (0–1140 pptv) and spring (0.5–3230 pptv). With an
exception for relatively lower HONO levels at altitudes higher than 2000 m
or in the free troposphere (Ye
et al., 2018), HONO mixing ratios are significantly higher at the summit of
Mt. Tai than at other mountain sites (Table 2). For
example, mean HONO mixing ratios observed at Mt. Whiteface in the USA
(Zhou et al., 2007) and Mt.
Hohenpeissenberg in Germany (Acker et al.,
2006) were 46 and 100 (daytime)/30 (nighttime) pptv, respectively. This
phenomenon could be explained by fewer human activities around these
mountains, while Mt. Tai is located in the middle of the NCP, with a relatively
high pollution level.
Note that high HONO mixing ratios were observed during the period from
14 to 26 July, with the co-occurrence of high SO2 (a
primary pollutant generally emitted at the ground level with a relatively
short lifetime). To better understand HONO formation and its role at
different pollution levels, data were classified into two periods: high HONO
period (HP; 14 to 26) and low HONO period (LP) that covers all
the other days. Statistics of observations during the two periods are
summarized in Table 1. Average HONO, NOy,
SO2, and PM2.5 during LP are 76 pptv, 4.7 ppbv, 0.3 ppbv, and 12 µgm-3, respectively, slightly lower than during HP (194 pptv, 7.0 ppbv, 0.8 ppbv, and 17 µgm-3, respectively).
HONO and related species measured at the summit of Mt. Tai during
the campaign.
Statistics of observations from 9 to 31 July 2018 at
the summit of Mt. Tai. High HONO period (HP): 14–26 July.
Low HONO period (LP): 9–13 and 27–31 July.
* Near or below the detection limit of the instrument used.
Summary of ground-based or aircraft-based HONO measurements at
background/remote sites (including mountain or pole sites) and cities near
Mt. Tai.
LocationAltitude (m)PeriodTechniqueMean (pptv)Range (pptv)HONO/NOx (%)ReferenceBackground sitesZugspitze, Germany26509–16 Jun 2001LOPAP12.6∗2–352.5∗Kleffmann et al. (2002)Cimone, Italy21658–17 May 2004Coil-HPLC0–40Beine et al. (2005)Hohenpeissenberg, Germany9803–12 Jul 2002, 29 Jun–14 Jul 2004Denuder-IC100a/30b< 10–2006.3cAcker et al. (2006)Whiteface, USA148314 Jun–20 Jul 1999Coil-HPLC46< 5–40023Zhou et al. (2007)Jungfraujoch, Switzerland35802–7 Nov 2005LOPAP7.5< 0.5–504.6Kleffmann and Wiesen (2008)Utqiaġvik (formerly Barrow), USA∼ 313 Mar–14 Apr 2009LOPAP27< 0.4–5006.0Villena et al. (2011)Concordia station, Antarctic Plateau (CSAP)323322 Dec 2010–18 Jan 2011LOPAP285–59Kerbrat et al. (2012)CSAP32339–23 Feb 2011LOPAP30–14Kerbrat et al. (2012)CSAP32334 Dec 2011–13 Jan 2012LOPAP35d/30eLegrand et al. (2014)Southeastern USPBL1 Jun–15 Jul 2013LPAP11.23–34Ye et al. (2018)Southeastern USFT1 Jun–15 Jul 2013LPAP5.61–15Ye et al. (2018)Mt. Tai15341–31 Dec 2017LOPAP1500–11403.2Jiang et al. (2020)Mt. Tai15345 Mar–8 Apr 2018LOPAP1300.5–32306.0Jiang et al. (2020)Mt. Tai15349–31 Jul 2018LOPAP1331–8806.4This studyNearby citiesJinan∼ 15026 Nov 2013–5 Jan 2016MARGA350< 3340Wang et al. (2015)Jinan∼ 1501 Sep 2015–31 Aug 2016LOPAP115017–83607.9a/5.6bLi et al. (2018)Tai'an∼ 15029 May–8 Jul 2018LOPAP62050–29704.2Xue et al. (2022)
∗ Data published in Kleffmann and
Wiesen (2008) and some unpublished data from the study of
Kleffmann et al. (2002).
a Noontime. b Nighttime. cHONO/NO2. d and
e Mean values in December and January, respectively.
PBL and FT: the planetary boundary layer and the free troposphere.
Impact of anthropogenic emissions on the measured HONOImpact of emissions at the summit level (1534 m a.s.l.)
High values of NOx/NOy are expected in a very fresh plume with
significant local emissions. Throughout the campaign, the average
NOx/NOy ratio was 0.43 ± 0.28, which was much lower than
fresh plumes observed in the nearest city of Tai'an, with an average of 0.93 ± 0.05 (from the measurements at the foot station), indicating an aged
air mass and a general small impact of nearby anthropogenic emissions at the
summit level.
However, regular local emissions may cause rapid increases in some
pollutants such as morning peaks. As an example, the most rapid increases in
HONO and other pollutants observed between 05:20 and 06:20 on 29 July
2018 are shown in Fig. 4. During this event, HONO
rapidly increased from 18 to 700 pptv, in concert with rises in NO, CO,
PM2.5, NOx, and NOy but a decrease in O3
(Table 3). The synchronous increase in NO (a primary
pollutant of combustion) and decrease in O3 indicate a relatively
fresh plume due to the fast titration reaction, as shown in
Reaction (R1):
NO+O3→NO2+O2k1.
During this event, air mass originated from the south (Fig. 2), the
polluted urban region (Fig. S1e in the Supplement) rather than the direction of the
potential sources at the summit level. This event lasted about 1.5 h
(05:20–06:50), much longer than the duration of the typical fresh plumes
observed at the foot station. Furthermore, the NO/NOx ratio of this
plume was 0.21, lower than that of the direct NO/NOx emission ratio of
∼ 0.9
(Carslaw
and Beevers, 2005; He et al., 2020; Kurtenbach et al., 2012; Wild et al.,
2017). This is also lower than that of the close-to-fresh plumes observed at
the foot station, with an average NO/NOx ratio of 0.46 ± 0.19 at
high O3 levels (Xue et al., 2022). Therefore, we could
conclude that the observed plume should originate from the foot urban region
rather than nearby emissions at the summit. The ΔHONO/ΔNOx within this plume was 8 %, much larger than that inferred from
direct emissions (typically inferred as less than 1 %). The ratio could be
enhanced by (1) nighttime NO2-to-HONO conversion at the ground level,
where the air mass was already aged before being transported to the summit
level; (2) in-plume NO2-to-HONO conversion along the mountain slope
(rock and vegetation surfaces, etc.); and (3) in-plume NO2-to-HONO
conversion on particle surfaces as both the boundary layer height (BLH)
elevation and the valley breeze are initialized after sunrise.
HONO and related species measured on the morning of 29 July
2018.
Concentrations of HONO and related species measured at 05:20 and
06:20 on 29 July 2018.
Species05:2006:20ΔHONO/pptv18700682CO/ppbv214659445NO/ppbv0.11.91.8NO2/ppbv0.47.16.7NOx/ppbv0.59.08.5NOy/ppbv0.413.312.9PM2.5/µgm-32.112.410.3O3/ppbv5951-8Impacts from the level below the summitInsight into the morning peaks of the diurnal profiles
In Fig. 5, the campaign averaged diurnal data are
shown, in which most observed species, including HONO, NO, NO2,
NOy, CO, and PM2.5, showed small peaks during 06:00–06:30. This
suggests a regular process responsible for this phenomenon rather than an
accidental event. Note that the sun started to rise and heat the ground
surface, as well as the mountain surface, 1 h before those peaks,
leading to an increasing BLH (Anisimov et
al., 2017). On the other hand, sunrise would initiate the daytime upslope
valley breeze wind
(Kalthoff
et al., 2000; Schmid et al., 2020; Ye et al., 1987), which could also be
supported by the increasing pressure and temperature (1 h after sunrise)
observed at the summit (Fig. S2). Hence, it can be inferred that the
morning peaks resulted from the rising air parcel, within which
pollutants accumulated during nighttime. Interestingly, similar morning
peaks were also observed in winter and spring (Fig. S3a), indicating the
persistent impact of this process.
Diurnal variations of HONO and related parameters observed at the
summit (orange) and the foot (blue) stations. Data for the summit station
have a time resolution of 10 min. Hourly PM2.5, NO2, and CO were
available but NO and NOy were not available at the foot station during
this period. All the data were in the same measurement period from 9
to 31 July, except for HONO, HONO/NOx, and J(NO2) for the
foot station measured from 29 May to 8 July.
Insight on the seasonal HONO variations
In addition to the morning peaks analysis, seasonal HONO variations at the
summit were also summarized (Figs. 6 and S3),
including measurements in winter, spring, and summer. Distinctly higher
PM2.5 and NO2 were observed in winter
(Fig. 6b and c) than in summer. However, HONO
levels in winter, spring, and summer were similar (Fig. 6a), indicating that the aerosol-derived sources did not dominate HONO
formation at the summit level. In general, HONO levels observed at the
ground level of the NCP were significantly higher in winter than in summer
(Li
et al., 2018; Nie et al., 2015; Xue et al., 2020). A similar HONO level
observed in summer was possible because of a more rapid vertical exchange
between the ground level and the summit level (see Sect. 3.2.3).
Statistic summaries of (a): HONO, (b): PM2.5, and (c):
NO2 in the three seasons. Error bars represent the standard deviation.
The top and the bottom of each diamond represent the 25 % and 75 %
percentages, respectively. The star and the line inside each diamond denote
the average and the median, respectively. Data for winter and spring was
taken from Jiang et al. (2020).
Insight on the comparison of pollutants at the foot and summit level
Comparison of daytime (05:00–18:00) average PM2.5, CO, O3, and
SO2 observed at the foot and the summit station is shown in
Fig. 7. It is apparent that all the average
daytime levels of primary pollutants (CO and SO2), partially primary
pollutant (PM2.5) and secondary pollutant (O3), show very similar
variation trends at both monitoring stations, revealing (1) a significant or
even dominant impact of pollutants at the foot level on that at the summit
level and (2) the presence of a pathway that enables the vertical air mass
exchange between the summit and the foot level. This is also consistent
with the higher daytime HONO (Fig. S3a) observed at the summit station in
winter than in summer because the regional pollution was generally much more
severe in winter than in summer.
In addition, during nighttime, the summit (∼ 1500 m altitude) is
above the boundary layer (in the residual layer), and similar variation
trends of pollutants were also found at the foot and the summit station
(Fig. S4), still indicating the presence of vertical air mass exchange at
night. This could also be inferred from the higher nighttime HONO (Fig. S3a) in summer than in winter because (1) more south winds (the direction to
Tai'an) were observed in summer (Fig. S5) and (2) the nocturnal
boundary layer height was generally much lower in winter than that in
summer.
Comparison of daytime (05:00–18:00) average (a) SO2, (b)
O3, (c) CO, and (d) PM2.5 observed at the foot (left axis in
blue) and summit (right axis in orange) stations during the same period from
9 to 31 July.
Impact from Tai'an (150 m a.s.l.)
Besides the discussion in Sect. 3.2.1, five arguments point to the
potential impact from pollution in the nearest city (Tai'an,
∼ 150 m a.s.l.) on the summit HONO level:
The “∩” shape of HONO variation in the daytime was different from
that of NO2 (a constant level during the daytime), NOy (which
increased in the early morning and then remained stable at noontime,
followed by a continuous increase in the late afternoon), and PM2.5
(which also showed a “∩” shape variation, but its peak was 3 h
later than the HONO peak). These observations indicate that the observed
HONO at the summit was not dominated by in situ aerosol-derived formation
(Fig. 5) but an external HONO source such as
transport.
High-level HONO was frequently observed at the ground level (150 m a.s.l.) in Tai'an (Table 2), and almost the
same variation trends of HONO/NOx were observed at both the summit and
foot stations (Fig. 5g).
HONO peaks at the summit occurred at noontime when the BLH was high and
valley breeze wind was strong.
High-level HONO (> 200 pptv) observed at the summit mainly
appeared when the air mass came from south or southwest (the direction to
Tai'an; see Fig. 8).
HONO peaks occurred synchronously with the peaks of SO2, which is
mainly emitted at the ground level, and NO2, which is an important HONO
precursor (Fig. 3).
The impact could be achieved through (1) the air mass ascended by valley
breeze upslope wind (daytime) and by the south wind (daytime and nighttime,
“Insight into the comparison of pollutants at the foot and summit level” in Sect. 3.2.2), and (2) HONO formation during the air mass ascending
process, i.e., HONO formation through the NO2 heterogeneous uptake on
the mountain slope surfaces
(George et al.,
2005; Marion et al., 2021; Stemmler et al., 2006). The HONO production from
the above processes is defined as P(HONO)transport and will be
discussed in Sect. 3.6.
Pollution rose plot of HONO against the wind direction. The
frequency contribution of counts by wind direction is also shown on the left
axis.
The length of the hypotenuse from the foot to the summit is about 4.2 km,
with an average elevation angle of about 20∘. In the daytime, the
valley breeze could occur with an upslope wind speed of 2–5 m s-1
reported in previous measurements
(Kalthoff
et al., 2000; Schmid et al., 2020; Ye et al., 1987; see also
https://glossary.ametsoc.org/wiki/Upvalley_wind, last access: 7 March 2022); it takes
about 14–35 min (ttransport) for the air mass to be transported from
the foot to the summit. The upslope valley breeze wind could transport
polluted air mass from the foot to the summit levels. This process could be
accelerated by the dominant south wind (Fig. 8) as
the urban site (150 m a.s.l.) is south of the summit station (1534 m a.s.l.). The mean south winds measured at the ground and summit stations are
> 2 and > 5 m s-1, respectively. Then the integrated wind speed along the mountain slope should be 4–10 m s-1,
and the calculated ttransport will be reduced to 7–17.5 min.
The key question is the quantity of HONO that still exists after transport
from the foot to the summit levels regarding its photolysis in the daytime.
Assuming first-order decay of HONO by photolysis during the transport, the
remaining HONO and its ratio at the summit can be calculated:
1ct=c0e-JHONO⋅ttransport,2α=ctc0=e-JHONO⋅ttransport,
where ct, c0, J(HONO), and α represent the remaining HONO
after a transport period (ttransport), the initial HONO concentration
at the foot, the HONO photolysis frequency, and the remaining proportion of
HONO.
Figure 9 shows the calculated α with
ttransport=7 or 17.5 min during the daytime. It is apparent that
α is larger than 43 % with ttransport=17.5 min and larger
than 72 % with ttransport=7 min, providing a theoretical basis
for the potential role of vertical HONO transport from the ground to the
summit level. The calculations do not consider the atmospheric dilution or
dispersion during the transport, which may reduce α. This effect
could be roughly quantified by comparing levels of long lifetime species
(e.g., CO) at the foot and the summit station. The measured hourly CO
averages at noon are 493 and 379 ppbv at the foot and the summit station,
respectively (Fig. 5). Taking the minima of CO
measurements at the summit station as the background CO level (167 ppbv),
we can obtain a dilution factor of 2.3. The dilution process may also
similarly affect HONO; i.e., α is expected to be reduced by a factor
of 2.3, leading to α values of > 31 % and > 19 % with ttransport=7 or 17.5 min, respectively. The above
calculation only included the daytime HONO sink through photolysis and
atmospheric dilution, but the sources, such as NO + OH and heterogeneous
NO2 reactions, were not considered, and hence, the calculated α
represents a lower limit. Thus, the impact of transport is expected to be
larger when (1) taking other HONO formation paths (e.g., NO2
heterogeneous reactions on the mountain surfaces and the vegetation
surfaces) into account, and (2) vegetation shadows on the mountain surface
slow down HONO photolysis during the transport. Therefore, ground-level
(∼ 150 m a.s.l.) HONO as well as its formation during
transport may affect the HONO measurement at the summit significantly. The
quantification of the contribution will be discussed in Sect. 3.6.
Diurnal profiles of the remaining proportion of HONO (α)
after a period of transport (ttransport) from the ground to the summit
levels and J(HONO) during the daytime.
Daytime unknown HONO source strength
The photostationary state (PSS), presented by the following equations, is
valid to calculate the unknown HONO source strength (Pun) when local
emission was negligible
(Crilley
et al., 2016; Kleffmann et al., 2005; Michoud et al., 2012). The predicted
HONO concentration by PSS ([HONO]PSS) and Pun can be calculated
by Eqs. (3) and (4),
respectively.
R2HONO+hν→NO+OH,J(HONO),R3NO+OH→HONO,k1=9.8×10-12cm3molecules-1R4HONO+OH→NO2+H2O,k2=6.0×10-12cm3molecules-13[HONO]PSS=k1×NO×[OH]JHONO+k2×OH,4Pun=(HONO-[HONO]pss)×(JHONO+k2×OH).
OH measurements were not available during this campaign. One popular
method used to estimate OH is based on the correlation between OH and solar
ultraviolet radiation (e.g., J(O1D)) (Rohrer and
Berresheim, 2006). Considering that Mt. Tai is surrounded by polluted
regions, empirical formulas between OH and J(O1D) from the ground or
other mountain measurements may not be reasonable here. In June 2006, Kanaya
et al. (2009) conducted a comprehensive field campaign at the summit of Mt. Tai. OH levels
and sources were studied by a box model. From the average diurnal variations
of the modeled OH and J(O1D), a significant correlation
(R2>0.9) between them was found, which was used here to
estimate OH concentrations. This method could lead to some uncertainties in
OH levels because (1) high correlations between OH and J(O1D) were found
in their average diurnal variations but may not be in their time series, and
(2) HONO was not constrained in the box model simulations, so OH could be
underestimated for the MTX 2006 campaign.
One way to consider HONO impact is to discuss the OH uncertainties caused by
the lack of HONO chemistry. Assuming that the impact of HONO on OH levels is
determined by its contribution to primary OH production, we can
preliminarily deduce the OH uncertainties at the summit station caused by
the lack of HONO chemistry based on measurements and model simulations for
the foot station. At the foot station, HONO photolysis contributed 64 % of
primary OH production (see Sect. 3.6). If the box model was not
constrained by the measured HONO, OH would be underestimated by 25 % (see
the companion paper, Xue et al., 2022). At the summit
station, HONO contributed 18 % of the primary OH production (see Sect. 3.6). Therefore, OH underestimation due to the lack of HONO chemistry at the
summit station should be roughly around 7 % or so.
Hence, to cover the uncertainties caused by the above issues, we added OH
sensitivity tests, reducing or increasing the OH level by 30 %, to
quantify the impact of the OH uncertainties in our further analysis and
conclusions. The OH used, the corresponding HONOpss, and Pun
results from the sensitivity tests are also shown in Fig. S6. The
estimated OH level was lower than that modeled during the MTX campaign
(Kanaya
et al., 2009, 2013). This is mainly caused by lower J(O1D) resulting
from frequent cloudy weather during the present study period. For instance,
the average RH during this campaign was 96 %, which is much higher than
that during the MTX campaign (67 %). Reducing or enlarging OH levels by
30 % indeed remarkably impacted HONOpss. However, HONOpss (5–15 pptv level) is still 1–2 orders of magnitude lower than the observed HONO
(50–200 pptv level), leading to a small impact of variable OH and
HONOpss levels on Pun. Hence, we highlight the uncertainties in OH
levels estimated by the current method, but its impact on following HONO
budget analysis should be small as discussed above.
The diurnal variation of the calculated noontime (10:00–16:00) Pun
is shown in Fig. 10. Campaign-averaged Pun
was about 290 ± 280 pptv h-1, with a maximum of about 1800 pptv h-1. The maximum Pun value appeared at midday (13:00), indicating
a photo-enhanced HONO source. High correlations (r=0.79, 0.83, or 0.83)
were found between Pun and NO2×J(NO2),
pNO3×J(HNO3), or NOy×J(HNO3)
(Table 4), suggesting the potential HONO formation
from photosensitized NO2 reactions or photolysis of NOz (NOz= NOy–NO–NO2) species such as particulate nitrate
(pNO3). Moreover, the relatively poor correlations (r=0.17 or 0.64)
between Pun and NO2×Sa or NO2×Sa×J(NO2) (Table 4) suggested
minor roles of dark and photo-enhanced NO2 uptake on the aerosol
surface in the HONO formation. In addition, a high correlation between Pun
and HONO (r=0.76) was obtained. A possible reason could be that HONO and
other pollutants were not dominated by in situ formation but by transport,
as discussed in Sect. 3.2.2. As correlation analysis is only a preliminary
indicator and it might not be instructive for HONO budget analysis when the
vertical air mass exchange occurs, further investigation of NO2 uptake
on aerosol surface and photolysis of pNO3 is presented in Sect. 3.4
and 3.5, respectively.
The correlation coefficients (r) between HONO or Pun and other
parameters (first column).
CorrelationsHONOPunCO0.20-0.10NO0.060.09NO20.530.05NOx0.520.06NOy0.490.45NOz0.380.49PM2.50.070.21HONO–0.76HONO⋅J(HONO)–0.988J(NO2)-0.040.77NO2× PM2.50.280.25NO2×J(NO2)0.030.79pNO3×J(HNO3)0.050.83NOy×J(HNO3)0.060.83NO2×Sa0.470.17NO2×Sa×J(NO2)0.100.64Constraint on HONO formation from NO<inline-formula><mml:math id="M431" display="inline"><mml:msub><mml:mi/><mml:mn mathvariant="normal">2</mml:mn></mml:msub></mml:math></inline-formula> uptake on the aerosol surface
During the daytime, the HONO production rate from the NO2 uptake on the
aerosol surface (P(HONO)a) with the photo-enhanced effect is
parameterized by the following equation. Note that dark NO2 uptake on
the aerosol surface was not considered due to a much lower uptake
coefficient generally at a level of 10-6
(George
et al., 2005; Han et al., 2017; Stemmler et al., 2006, 2007).
P(HONO)a=v(NO2)×Sa×[NO2]4×γa×J(NO2)measured0.005s-1,
where ν(NO2), Sa, γa, and
J(NO2)measured/0.005 are the molecular speed of NO2 (m s-1), aerosol surface density (m-1), the photo-enhanced uptake
coefficient of NO2 on the aerosol surfaces, and the photo-enhancement
factor normalized to a J(NO2)=0.005 s-1. In
Eq. (5), an upper limit HONO yield for the NO2
conversion of 100 % was assumed. Additionally, RH was proposed to
significantly influence aerosol surface density, especially at our site,
with frequently high RH up to 100 %. Then besides calculating the aerosol
surface density based on the measured aerosol size distribution
(Sa_measured), we estimated the effective aerosol
surface density per meter with an RH enhancement factor fRH (Sa=Sa_measured×fRH) using the following equation:
fRH=1+a×(RH/100)b,
where a and b are empirical values of 2.06 and 3.60, respectively
(Liu et al.,
2008). The average Sa without and with RH enhancement is 3.0 × 10-4 and 8.3 × 10-4 m-1, respectively. Note that the
uncertainty of Sa is not expected to cause a significant uncertainty on
HONO budget analysis as P(HONO)a was not the dominant source
(Fig. 10, and see the discussion below on
P(HONO)a contribution).
As Pun includes all the sources except NO + OH, then P(HONO)a≪Pun can always be obtained. Hence, the real γa value should be much lower than the values inferred (γa_inferred) from Pun=P(HONO)a. In total,
606 γa values were inferred based on the measurements, varying
from 1.3 × 10-4 to 8.5 × 10-3, with a mean of (8.3 ± 7.5) × 10-4. However, the minimum (γa_inferred_mini) of 1.3 × 10-4 is still very high, compared to the results of most lab studies,
in which values of γa of typically a few times 10-5 or
even less were observed
(Han
et al., 2016; J. Liu et al., 2019; Ndour et al., 2008; Sosedova et al., 2011;
Stemmler et al., 2007). Hence a popularly used value of γa=2× 10-5 was used to calculate P(HONO)a, and γa_inferred_mini of 1.3 × 10-4 was also used for uncertainty analysis as the upper limit.
The calculated P(HONO)a with these γa values is shown in
Fig. 10. It is obvious that P(HONO)a is
significantly lower than Pun with either lab-based γa=2× 10-5 or even γa_inferred_mini= 1.3 × 10-4, pointing out the
minor role of NO2 uptake on the aerosol surface in daytime HONO
formation. With the lab-based γa=2× 10-5,
P(HONO)a could only explain 3 % of Pun, which is similar to
previous model studies
(Y. Liu
et al., 2019; Xue et al., 2020; Zhang et al., 2016). The contribution of
P(HONO)a to Pun increased when using γa_inferred_mini but resulted from an overestimated γa as discussed before. Nevertheless, analysis in this study still
could be an important effort in the field constraints on the
NO2-to-HONO conversion on the aerosol surface.
Unknown HONO source strength (Pun) and HONO production
rates from NO + OH (P(HONO)NO+OH), NO2 uptake on the aerosol
surface (P(HONO)a) with the inferred γa_inferred_mini=1.3 × 10-4 and the popular
used γa=2× 10-5), and nitrate photolysis
(P(HONO)nitrate) with EF values of 1, 7, and 15.6.
Constraint on HONO formation from the photolysis of particulate nitrate
As one of the important inorganic components of aerosols, particulate
nitrate (pNO3) could undergo photolysis, with the production of HONO.
This process needs more field constraints as discussed in the Introduction. During the present campaign, pNO3 at the summit was measured
by a filter method every 2 h (Liu et al., 2020), but it
suffered a sampling problem after 12 July. Because NOz (NOz= NOy–NO–NO2) mainly contains pNO3 and its precursors,
e.g., HNO3 and N2O5, similar variations are expected between
NOz and pNO3. As shown in Fig. S7, NOz and pNO3
exhibited a very high correlation (R2=0.895), for which pNO3
makes 44 % of NOz, and this fraction was used to estimate pNO3 in
the period when it was not measured. The uncertainty of the estimated
pNO3 should have no significant impact on daytime HONO formation
concerning its small contribution to daytime HONO formation (see Sect. 3.6).
A high correlation between Pun and pNO3×J(HNO3) was
found (Table 4), suggesting a possible impact of
pNO3 on HONO formation. But one should bear in mind that the high
correlation might also be caused by the remarkable impact on pNO3
formation from HONO-related reactions (e.g., HONO ⟶hν OH ⟶NO2
HNO3→pNO3)
(Xue et al., 2020) or other
photolytic processes. For parameterization, an enhancement factor (EF) was
defined as the ratio of photolysis frequencies of pNO3 to gas-phase
HNO3. Then HONO production from pNO3 photolysis
(P(HONO)nitrate) could be quantified by Eq. (7):
P(HONO)nitrate=pNO3×J(HNO3)×EF.
Similar to NO2 uptake on the aerosol surface, one can always find
P(HONO)nitrate≪Pun. Hence, it is expected that
the real EF should be much lower than the inferred values (EFinferred)
from P(HONO)nitrate=Pun. Therefore, 606 EF values were
inferred, in the range of 15.6 to 1072, with a mean of 173 ± 98, which
is much higher than values (around 1) determined in recent flow tube or smog
chamber studies (Shi et al., 2021; Wang
et al., 2021). The minimum (EFinferred_mini=15.6) is
at a similar level to field studies of
Romer et al. (2018) and
Zhou et al. (2003) and the lower values in the
laboratory studies
(Bao
et al., 2018; Ye et al., 2016, 2017; Zhou et al., 2011). To quantify the
HONO production from pNO3 photolysis, the EF value of 7 from a recent
field study (Romer et al., 2018)
was used for P(HONO)nitrate calculation, and
EFinferred_mini (15.6) from this study and EF values of
∼ 1 from recent laboratory studies
(Shi et al., 2021; Wang et al., 2021)
were also used for the uncertainty analysis and comparison.
The calculated P(HONO)nitrate with these EF values is shown in
Fig. 10. With EF = 7, P(HONO)nitrate was at
a level of half of NO + OH but much lower than Pun, which was also
observed at the summit of Mt. Whiteface
(Zhou et al., 2007). P(HONO)nitrate
could explain 4.3 % of the observed Pun. Its contribution varied from
0.6 % to 9.6 %, depending on EF values varying from 1 to 15.6 in the
sensitivity tests. Therefore, with a P(HONO)a (γa=2× 10-5) contribution of 3 % (Sect. 3.4) and a
P(HONO)nitrate (EF = 7) contribution of 4.3 %, the other sources
(defined as P(HONO)other=Pun-P(HONO)a-P(HONO)nitrate, mainly transported from the ground level as discussed
in Sect. 3.2.2) made a dominant contribution of 92.7 % to the observed
Pun.
Moreover, significant differences between EF values obtained from field
studies and laboratory studies indicate a complex process of pNO3
photolysis that may be influenced by various environmental parameters, e.g.,
the aerosol pNO3 loading and the aerosol composition
(Bao
et al., 2018, 2020; Ye et al., 2016, 2017), and experimental laboratory
conditions, e.g., collected particles on the filter or generated airborne
particles (Shi et al., 2021; Wang et al.,
2021). We therefore suggest that this process still needs further field or
laboratory constraints. To the best of our knowledge, this study provided the first
field constraint on the aerosol-derived HONO sources in the NCP region,
where the abundance of aerosol was frequently observed, and its role in HONO
formation is still highly controversial.
The landscape (e.g., mountains) enhances the vertical air mass exchange,
leading to a weak vertical HONO distribution within the boundary layer,
which is not yet considered in previous studies (Jiang et
al., 2020). This will underestimate the role of ground-derived sources in
HONO formation in the upper boundary layer over mountain regions. Radicals,
including OH and HO2, are not expected to be transported far due to
their short enough lifetimes (< 100 s). However, 15 % of daytime
HONO was formed at the ground level through NO + OH as reported in the
companion ACP paper (Xue et al., 2022), and part of OH
consumed at the ground level would be released at the summit level through
HONO photolysis. Hence, it could be preliminarily inferred that radicals
(i.e., OH) could be transported through their precursors/reservoirs (like
HONO) with lifetimes longer than themselves. Furthermore, the enhanced
vertical air mass exchange could also lead to fast transport of other
pollutants (PM2.5, O3, CO, SO2, etc.) from the ground to the
summit level, which will significantly impact the atmospheric composition
as well as its chemistry in the upper boundary layer or the residual layer.
The discussion and implications in this study are instructive for further
field and model studies.
OH production from photolysis of HONO
(P(OH)HONO_net) and O3 (P(OH)O3) at the foot
and the summit of Mt. Tai. (a)P(OH)HONO_net, (b) relative contributions, and (c)P(OH)O3.
Role of HONO in the oxidizing capacity of the lower and the upper
boundary layer
O3 was typically the major OH source in high-altitude regions,
including the upper boundary layer. Then we compared the OH production rates
from O3 and HONO photolysis to investigate whether HONO could play a
significant role in the oxidizing capacity of the atmosphere at this
high-altitude site. Photolysis of HONO and O3 with their net OH
production is shown in Reactions (R2) and
(R5) to (R7), respectively. OH
loss through HONO + OH and NO + OH was subtracted from P(OH)HONO to
obtain P(OH)HONO_net.
R5O3+hυ→O2+O(1D),J(O(1D))R6O(1D)+H2O→2OH,k3R7O(1D)+MN2orO2→O(3P)+MN2orO2,k4R8P(OH)HONO_net=HONO⋅JHONO-k1⋅NO⋅[OH]-k2⋅HONO⋅[OH],R9P(OH)O3=O3⋅J(O(1D))⋅ϕ,
where the reaction constants were taken from the IUPAC kinetic database
(https://iupac-aeris.ipsl.fr, last access: 7 March 2022). The atmospheric RH and
temperature largely influenced the branching ratio of
Reactions (R6) to (R7). The average OH
yield (ϕ) during the campaign of 20 % was used for calculating OH
production from O3 photolysis.
Additionally, in the companion paper, HONO was reported as the most important
primary OH source at the foot station (Xue et al., 2022). A
comparison between the roles of HONO at the foot and the summit station
could provide more insights into the importance of HONO throughout the
boundary layer. Moreover, as reported in the companion paper, HONO observed
at the foot station was mainly produced through NO2 heterogeneous
reactions and NO+OH. Therefore, the comparison could also shed light on
the link between the atmospheric oxidizing capacity in the lower and the
upper boundary layer, although measurements at two stations were conducted
during two consecutive periods rather than the same one in summer 2018.
Figure 11 displays the diurnal profiles of net OH
production rates from HONO and O3 photolysis at the foot and the summit
station. Both P(OH)HONO_net and P(OH)O3 showed
higher levels at the foot station compared to the summit station. For
instance, average P(OH)HONO_net and P(OH)O3 at the
foot station are 0.9 and 0.5 ppbv h-1, respectively, both of which are
significantly higher than those (0.06 and 0.28 ppbv h-1) at the summit
station. This is caused by relatively low HONO and O3 concentrations
and lower solar photolysis frequencies as a result of frequent cloud
formation observed at the summit station.
In particular, after nighttime accumulation, HONO photolysis is found to
initialize daytime photochemistry in the early morning at the ground level
(Alicke
et al., 2002; Kleffmann, 2007; Platt et al., 1980). This was also observed
at the foot station. As shown in Fig. S8, at the foot station, the
contribution of P(OH)HONO_net to P(OH)sum was
almost 100 % at sunrise around 05:00. It showed a declining trend but still
played the dominant role in P(OH)sum, with a contribution larger than
90 % in the early morning (05:00–07:00). At the summit station, at 05:00,
solar radiation was very weak, for instance, J(NO2) was only
3.6 × 10-4 s-1. At this time, P(OH)HONO_net was slightly negative (-7 × 10-3 ppbv h-1) due to OH
loss through HONO + OH and NO + OH. O3 photolysis was initialized
at the same time, but P(OH)O3 was nearly zero (7 × 10-4 ppbv h-1). From 06:00 to 07:00, a considerable amount of net OH was
produced through HONO photolysis (0.04–0.09 ppbv h-1), with its
contribution to P(OH)sum decreasing from 64 % to 39 % (Fig. S8).
Hence, it could be inferred that daytime atmospheric photochemistry at the
summit level is also initialized by HONO photolysis.
On average, the contribution of P(OH)HONO_net to
P(OH)sum was 64 % at the foot station, higher than that at the summit
station (18 %), indicating the essential role of HONO in the atmospheric
oxidizing capacity at both the ground (lower boundary layer) and the summit
(upper boundary layer) level in mountainous regions. As discussed before,
the transport from the ground to the summit level contributed to the
majority of HONO observed at the summit level. This points to a new insight
that ground-derived HONO plays an important role in the oxidizing capacity,
not only at the ground level, but also in the upper boundary layer
(∼ 1500 m) in mountainous regions. Yet this vertical exchange
might only be valid in the mountainous areas, and the follow-up regional
impact still needs to be quantified by further model studies.
Summary
Observations of HONO and related parameters at the summit of Mt. Tai (1534 m a.s.l.) in July 2018 were presented. The average HONO mixing ratio is 133 ± 106 pptv, with a maximum of 880 pptv, significantly higher than
observations at other mountain summits worldwide. Along with observations at
the ground level (the nearest city, Tai'an), HONO formation from
different paths and its role in the atmospheric oxidizing capacity of the
upper boundary layer were explored and discussed.
The main conclusions are listed as follows:
Constraints on the kinetics of NO2 uptake coefficient on the aerosol
surface and photolysis of pNO3 were obtained based on the assumption
that Pun could be solely explained by NO2 uptake on the aerosol
surface, P(HONO)a, or particulate nitrate photolysis,
P(HONO)nitrate. The inferred γa and EF values were much
higher than most values obtained from recent laboratory studies, indicating
that aerosol-derived HONO could not explain the observed Pun. In
the NCP region, the abundance of aerosol was frequently observed, but its
role in HONO formation is still highly controversial as a result of
uncertain kinetics. This study provided the first field constraints on
aerosol-derived HONO sources in this region and will be instructive for
further laboratory or model studies.
With a γa value of 2 × 10-5 and an EF value of 7,
P(HONO)a and P(HONO)nitrate showed small contributions (3 % and
4.3 %, respectively) to daytime HONO formation at the summit station. Both
P(HONO)a and P(HONO)nitrate varied from negligible to moderate
levels (similar to NO + OH), depending on γa and EF values,
suggesting the necessity to further study the related kinetics.
Additionally, although high values of γa (1.3 × 10-4) and EF (15.6) compared with recent studies were tested here, both
sources were still much lower than the observed Pun. The remaining
majority (92.7 %) of Pun was dominated by the rapid vertical
transport from the ground to the summit level, including heterogeneous HONO
formation on surfaces of the mountain slope, which was inferred from
comprehensive evidence presented in this study.
A comparison of HONO contributions to primary OH at the summit and the foot
level was conducted. It was confirmed that HONO photolysis initialized
daytime photochemistry at both sites in the early morning. On average, HONO
made contributions of 64 % and 18 % to P(OH)sum at the foot and the
summit level, respectively, indicating the important role of HONO in the
oxidizing capacity of the atmosphere in mountainous areas. HONO formation at
the ground level could significantly influence the HONO mixing ratios and
the atmospheric oxidizing capacity at the summit level through vertical
air mass exchange. Moreover, the enhanced vertical air mass exchange could
also lead to a fast exchange of other pollutants between the ground and the
summit levels, which significantly impacts the atmospheric composition as
well as the chemistry in the upper boundary layer or the residential layer.
However, those follow-up impacts, by far, are not quantified by the current
model studies.
Data availability
All the summertime data used in this study are
available upon request from the corresponding authors.
The supplement related to this article is available online at: https://doi.org/10.5194/acp-22-3149-2022-supplement.
Author contributions
CX, CY, CZ, YZ, HL, and ZG
performed the field measurements. CX analyzed the observation data
and wrote the paper with inputs from all co-authors. CY and JK helped
with the data analysis and manuscript writing. JK, CY, VC, AM, LX,
JC, KL, FB, and YM revised the manuscript.
Competing interests
The contact author has declared that neither they nor their co-authors have any competing interests.
Disclaimer
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Acknowledgements
We are grateful to Xiaowei He, Pengfei Liu, Chao Zhu, Jiarong Li, Hui Chen,
Xianmang Xu, Hongyong Li, Pengcheng Zhang, and Jinhe Wang for their help with
the measurements at the summit of Mt. Tai. We thank all researchers involved
in this campaign from the Research Centre for Eco-Environmental
Sciences, Chinese Academy of Sciences, Fudan University, Shandong Jianzhu
University, Shandong University, and the Municipal Environmental Protection
Bureau of Tai'an. We thank Yunqiao Zhou for his help with the map plotting.
We thank the two anonymous reviewers and the editor, Yugo Kanaya, for their
efforts towards improving our manuscript.
Financial support
This work was supported by the National Natural Science
Foundation of China (grant nos. 41727805, 91544211, 41975164, and 21876186) and
the PIVOTS project provided by the Region Centre – Val de Loire (ARD 2020
program and CPER 2015 – 2020).
Review statement
This paper was edited by Yugo Kanaya and reviewed by two anonymous referees.
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