Nitrous acid (HONO) in the core city of the Central Plains Economic Region in China was measured using an ambient ion monitor from 9 to 31 January 2019.
Measurement time intervals were classified into the following periods in
accordance with the daily mean values of PM2.5: clean days (CDs),
polluted days (PDs), and severely polluted days (SPDs). The HONO
concentrations during CD, PD, and SPD periods were 1.2, 2.3, and 3.7 ppbv,
respectively. The contributions of the homogeneous reaction, heterogeneous
conversion, and direct emissions to HONO sources varied under different
pollution levels. The mean values of the net HONO production of the
homogeneous reaction (POH+NOnet) in CD,
PD, and SPD periods were 0.13, 0.26, and 0.56 ppbv h-1, respectively.
The average conversions of NO2 (CHONO) in CD, PD, and SPD periods
were 0.72×10-2, 0.64×10-2, and 1.54×10-2 h-1, respectively, indicating that the heterogeneous
conversion of NO2 was less important than the homogeneous reaction.
Furthermore, the net production of the homogeneous reaction may have been
the main factor in the increase of HONO under high-NOx conditions
(i.e., when the concentration of NO was higher than that of NO2) at
nighttime. Daytime HONO budget analysis showed that the mean values of the
unknown source (Punknown) during CD, PD, and SPD periods were 0.26,
0.40, and 1.83 ppbv h-1, respectively. The values of
POH+NOnet, CHONO, and Punknown
in the SPDs period were comparatively larger than those in other periods,
indicating that HONO participated in many reactions. The proportions of
nighttime HONO sources also changed during the entire sampling period.
Direct emissions and a heterogeneous reaction controlled HONO production in
the first half of the night and provided a contribution that is larger than that of
the homogeneous reaction. The proportion of homogenization gradually
increased in the second half of the night due to the steady increase in NO
concentrations. The hourly level of HONO abatement pathways, except for OH + HONO, was at least 0.22 ppbv h-1 in the SPDs period. The cumulative
frequency distribution of the HONOemission/HONO ratio (less than
20 %) was approximately 77 %, which suggested that direct emission was
not important. The heterogeneous HONO production increased when the relative
humidity (RH) increased, but it decreased when RH increased further. The
average HONO/NOx ratio (4.9 %) was more than twice the assumed
globally averaged value (2.0 %).
Introduction
Nitrous acid (HONO) is important in the photochemical cycle and can provide
hydroxyl radicals (⚫OH; Harrison et al., 1996) as follows:
HONO+hv→⚫OH+NO(300nm<λ<405nm).
According to measurement and simulation studies (Alicke et al.,
2002), the contribution of HONO to ⚫OH concentrations can reach
25 %–50 %, especially when the concentration of OH radicals produced by
the photolysis of ozone, acetone, and formaldehyde is relatively low (2–3 h after sunrise; Czader et al., 2012). HONO
photolysis was the most important primary source of ⚫OH that
contributed up to 46 % of the total primary production rate of radicals
for daytime conditions (Tan et al., 2018). ⚫OH is an
important oxidant in the atmosphere, and it can react with organic
substances, control the oxidation capacity of the atmosphere, and accelerate
the formation of secondary aerosols in the urban atmosphere
(Sörgel et al., 2011). Therefore, the changes in the
contribution of the homogeneous reaction, heterogeneous conversion, and
direct emissions during pollution can be observed by studying the formation
mechanism of HONO.
Several instruments have been used to determine ambient HONO concentrations,
and these include the following: a differential optical absorption spectrophotometer (DOAS; Elshorbany et al., 2012; Winer and Biermann, 1994); a long path absorption
photometer (LOPAP; Heland et al., 2001); a wet chemical
derivatization technique (HPLC) coupled with UV–VIS detection (collectively HPLC/UV–VIS; Michoud et al., 2014); a stripping coil–UV/VIS
absorption photometer (SC–AP; Pinto et al., 2014); an incoherent broadband cavity-enhanced absorption spectroscope (IBBCEAS; Duan et al.,
2018); a chemical ionization mass spectrometer (CIMS; Hirokawa et al., 2009; Roberts et al.,
2010); and an ambient ion monitor (AIM; VandenBoer et al., 2014). A result comparison of the different instruments showed that the SC–AP is compatible with two
spectral measurement instruments, namely LOPAP and DOAS
(Pinto et al., 2014). Compared to HONO measured by the SC–AP deployed on site, HONO measured by AIM has a small
error and is within the acceptable analytical uncertainty (VandenBoer et
al., 2014). Previous studies have reported that HONO concentrations range
from a few parts per trillion by volume (pptv) in clean, remote areas to several parts per billion by volume (ppbv; 0.1–2.1 ppbv) in
air-polluted urban areas (Hou et al., 2016; Michoud et al., 2014).
The sources of HONO are direct emissions and homogeneous and heterogeneous
reactions (Acker et al., 2005; Grassian, 2001; Kurtenbach et al., 2001).
HONO can be directly discharged into the atmosphere during vehicle operations
and biomass combustion. Through a tunneling experiment, Kurtenbach et al. (2001) discovered that motor vehicles emit a small amount of HONO, and
the HONO/NOx ratio of HONO combustion sources (aside from NOx and
other pollutants) is 0.1 %–0.8 %. Another study showed that the homogeneous
reaction of NO and OH radicals is a major source of HONO under increased
NO concentrations (Spataro et al., 2013).
Furthermore, HONO can react with the ⚫OH (Alicke et al., 2003;
Vogel et al., 2003). Tong et al. (2015) used NO+OH and HONO+OH homogeneous reactions to calculate the net generation rate of HONO
homogeneous reactions at night, which are expressed as follows:
R2NO+⚫OH→HONOR3HONO+⚫OH→NO2+H2O.
Such calculations have been applied in studies on homogeneous reactions and
daytime budgets (Hou et al., 2016; Huang et al., 2017). These are studies
of homogeneous reactions, and some researchers have begun to explore the
mechanism of NO2 heterogeneous reactions. Finlayson-Pitts
et al. (2003) studied the mechanism of chemical adsorption of NO2, and H ions were revealed on the adsorbed surface by using isotope-labeled water as follows:
2NO2+H2O→HONO+HNO3.
In China, most studies of HONO have been focused on the Yangtze River
Delta, Pearl River Delta, and Jing-Jin-Ji region. For example, Hao
et al. (2006) reported that field measurement results, especially
HONO/NO2 and relative humidity (RH), have a significant correlation and
proved that heterogeneous reactions are an important source of nighttime
HONO. Although the specific chemical mechanisms of heterogeneous reactions
remain unknown, the intensity of HONO formation by NO2 can be expressed
by the HONO conversion frequency (Alicke et al., 2002; Li et al., 2012).
Su et al. (2008a) revealed the importance of the ⚫OH
from HONO during daytime (09:00–15:00 local time or LT) and found that many
unknown sources that are closely related to the solar radiation lead to
HONO formation. The unknown sources of HONO may include the NO2
photolysis of sooty surfaces and adsorbed nitric acid and nitrate at UV
wavelengths (Kleffmann et al., 1999). The homogeneous nucleation of
NO2, H2O, and NH3 is the HONO-formation pathway
(Zhang and Tao, 2010). Meanwhile, HONO can deposit and
react with amines to form nitrosamines
(Li et al., 2012) for sinking. The method
of budget analysis needs to include the HONO sources and sinks. Researchers suggested that the method of budget analysis is crucial for
obtaining the missing source. Spataro et al. (2013) measured the HONO level in Beijing's urban area and discussed the
spatiotemporal changes, meteorological effects, and contributions of HONO
from different sources. They used the measured HONO data to compare
pollution periods in Beijing's urban and suburban areas. Tong et al. (2015)
discovered that the pathway of the HONO-formation mechanism, namely direct
emissions, heterogeneous formation, and homogeneous reaction, is the same, but
the pathway is different at the two sites. A few studies (Cui et al.,
2018; Hou et al., 2016) compared the characteristics and sources of HONO
during severe pollution periods and clean periods. Although the definitions of the
two periods are different, both can be used to analyze the diurnal
variation, source, and daytime budget of HONO during the aggravation of
pollution.
There is no study of HONO in the Central Plains Economic Region (CPER) in China, with
a total population of 0.18 billion at the end of 2011. CPER is an important
region for food production and modern agriculture, as published by the Chinese government
(http://www.gov.cn/zhengce/content/2011-10/07/content_8208.htm, last access: 10 September 2019). The document described the different factors that affect atmospheric
pollution, including the level of economic development, energy structure,
industrial structure, and geographical location (solar radiation) in the
Yangtze River Delta, Pearl River Delta, and Jing-Jin-Ji region. As the core
city of CPER, Zhengzhou is characterized by severe PM (particulate matter)
pollution (Jiang et al., 2017, 2018d) and is thus selected for this study. In
recent years, comprehensive PM research has been conducted on the chemical
characteristics of PM in Zhengzhou (Jiang et al., 2018b; Li et al.,
2019) regarding source apportionment (Jiang et al., 2018c, e; Liu et al.,
2019), health risks (Jiang et al., 2019a, b), and emission-source
profiles (Dong et al., 2019; Jiang et al., 2018a). However, no study has
been performed on the sources and characteristics of HONO in Zhengzhou.
Moreover, no synthetic research on different pollution levels in the area is
available. In the current study, AIM was used to sample and analyze HONO
concentrations. The interactions between HONO and other factors, such as
PM2.5 during pollution, were assessed to understand the formation, influence, and removal of HONO on different pollution periods. The levels
of PM2.5 were divided into three periods to analyze the HONO sources,
sinks, and reactions in different periods. Many papers (Huang et al.,
2017; Tong et al., 2016) took PM2.5 as the main control factor of HONO
and studied the differences between HONO sources and characteristics during
clean and polluted periods. No homogeneous reaction, direct emission,
heterogeneous reaction, or daytime budget analysis was conducted during
the period of worsening pollution (named the HD period in this paper). Total
NOx emissions in cities with different leading factors of emissions
have been declining year by year due to the Chinese government's emission control
measures, but some Chinese cities are still in high-NOx areas (e.g., Beijing, Shanghai, Guangzhou, and Zhengzhou; Kim et al., 2015; Liu et
al., 2017). Under high-NOx conditions, some papers (Cui et al.,
2018; Hou et al., 2016) suggested that the heterogeneous reaction was the main
source of HONO and did not conduct a quantitative analysis of homogeneous
reaction – especially in winter. So, we explore relevant studies of
homogeneous reactions. In addition, the source contributions of HONO that varied with the degree of pollution at night were not explained. RH was
also analyzed to provide a detailed understanding of HONO-generation
intensity under different RH conditions. Analysis of the sources of HONO at
night provides strong support for conducting HONO budget analysis during the
daytime. To the best of the authors' knowledge, the formation
characteristics of HONO at continuous and high time resolutions and
different pollution levels have not been studied in Zhengzhou. This work can
assist the governments of the CPER in formulating a policy to decrease the
level of HONO precursors, i.e., NO and NO2, and direct HONO emissions from vehicles.
Experiment and methodsSampling site and period
The sampling site is on the rooftop (sixth floor) of a building at Zhengzhou
University (34∘48′ N, 113∘31′ E), which is located in
the northwestern part of Zhengzhou, China. The observation height is about
20 m from the ground, and the observation platform is relatively open and
without any tall buildings around. The site is about 500 m from the West
Fourth Ring Road of Zhengzhou and about 2 km from the Lian Huo
Expressway to the north. The measurement period was from 9 to 31 January
2019. Daily data were divided into two periods, namely daytime (07:00–18:00 LT) and nighttime (19:00–06:00 LT, i.e., the morning of the next day).
Instruments
AIM (URG-9000D, Thermo Fisher Scientific, USA), an online ion chromatographic monitoring
system for particle and gas components in the atmosphere, was used to
measure HONO concentration continuously at a temporal resolution of 1 h. The
atmospheric airflow entered the PM2.5 cyclone cutting head through the
sample tube, and gas–solid separation was performed with a parallel plate
denuder with a new synthetic polyamide membrane. The denuder had no moving
parts and could be changed without stopping the sampler. HONO was absorbed
by the denuder with an absorption liquid (5.5 mol m-3H2O2).
The chemicals that could be oxidized were absorbed by H2O2 on the
porous membrane surface, but several gases (e.g., O2 and N2) were
expelled by the air pump. The abundance of other gaseous acids and bases
affected the efficiency of HONO collection by AIM due to the relationship
between Henry's law constant and pH. This measurement method and its details
have been successfully evaluated in many field studies (Markovic et al.,
2012; Wang et al., 2019; Yang et al., 2020), as shown in the Supplement. In
addition, a QXZ1.0 automatic weather station (Yigu Technologies, China) was
used for the synchronous observation of meteorological parameters, including
temperature (T), RH, wind direction (WD), and wind speed (WS). The temporal
resolution of the model analysis system that integrates these types of observation instruments (TE – used for measuring O3; 48i – used for measuring CO; 42i – used for measuring NO, NOx, and NO2]; and
TEOM 1405 PM2.5 monitor – used for measuring PM2.5; Thermo
Fisher Scientific, USA) is 1 h. Detailed information can be found in the work of
Wang et al. (2019). Measurement technique,
detection limit, and accuracy of measured species are shown in Table S1 in the Supplement.
During the sampling period, all instruments were subjected to strict quality
controls to avoid possible contamination. The instrument accessories and
sampling process were periodically replaced and calibrated, respectively.
The instrument parts and consumables were changed before the observation
process, and the sampling flow was calibrated to reduce the negative effect
of the accessories. Before this measurement period, the membrane of the denuder
was replaced and standard anion and cation solutions were prepared
on 3 January. The standard curve should be drawn to ensure the
appropriateness of the correlation coefficient (≥0.999) and the
accuracy of the sample retention time and response value. The minimum
detection limit of AIM was 0.004 ppbv. Other detailed information can be
found in the work of Wang et al. (2019).
Results and discussionTemporal variations of meteorological parameters and pollutants
The daily changes in the meteorological parameters and PM2.5 are shown in
Fig. 1. In accordance with the daily average concentration level of
PM2.5, the analysis and measurement process was divided into three
periods (clean days – CDs, polluted days – PDs, and severely polluted days – SPDs). The days on which the daily averages of PM2.5 were lower than
the daily average of the second grade of the Chinese National Ambient Air Quality
Standards (CNAAQS; 75 µg m-3) represented CDs (9, 16, 17,
21, 22, 23, 26, and 31 January), with RH ranging from 5 % to 79 % and WS ranging
from 0 to 4.2 m s-1. The days on which the daily averages of PM2.5
were between 75 and 115 µg m-3 represented PDs (10, 15, 18,
20, 25, 27, and 28 January), with RH ranging from 17 % to 86 % and WS ranging from 0
to 4.6 m s-1. The days on which the daily averages of PM2.5 were
higher than 115 µg m-3 represented SPDs (11, 12, 13, 14,
19, 24, 29, and 30 January), with RH ranging from 30 % to 96 % and WS ranging from 0
to 3.5 m s-1. Northwesterly or easterly wind was observed in most of the
observation periods, except for 21–22 January. WD was northerly, the maximum WS
reached 4 m s-1, the PM2.5 concentration decreased rapidly, and the
effect of pollutant removal was evident. Table 1 lists the data statistics
of HONO, PM2.5, NO2, NO, NOx, HONO/NO2, HONO/NOx,
O3, CO, T, RH, WS, and WD during the measurement period, together with
the mean value ± standard deviation. The meteorological parameters
in Table 1 show that the average RH in CD, PD, and SPD periods was 33 %, 49 %,
and 68 %, respectively. In SPDs, RH was high and WD was low (mean value of
0.4 m s-1).
Temporal trends of hourly averages for T, RH, WD, WS, and PM2.5
during the measurement. (The shaded areas are as follows: white for the CDs period; gray for
the PDs period; and red for the SPDs period.)
Data statistics of HONO, PM2.5, NO2, NO, NOx, HONO/NO2, HONO/NOx, O3, CO, T, RH, and WS during the measurement period; mean value ± standard deviation.
Temporal variations of hourly averages for HONO, NO, NO2, O3,
and CO during the measurement. (The shaded areas are as follows: white for the CDs period;
gray for the PDs period; and red for the SPDs period.)
In accordance with the data on trace gases, the average HONO values in CD,
PD, and SPD periods were 1.1, 2.3, and 3.7 ppbv, respectively. The mean values of
NO2 were 25, 33, and 42 ppbv (46, 63, and 78 µg m-3 lower
than the first grade of the CNAAQS; [80 µg m-3]), respectively. The
mean values of CO were 1, 1, and 2 ppmv (1, 2, and 2 mg m-3 lower than
the first grade of the CNAAQS; [4 mg m-3]), respectively. Figure 2 shows the
concentration changes in HONO and gas species throughout the measurement
period. The variations of the average HONO, PM2.5, NO2, and CO in
the three periods were similar. The mean values of all pollutant
concentrations, except O3, in the SPDs period were the largest, and those values
in the CDs period were the smallest. The highest mean value of O3
occurred in the CDs period, which is similar to previous observations (Hou et al.,
2016; Huang et al., 2017; Zhang et al., 2019).
The HONO concentrations ranged from 0.2 to 14.8 ppbv and had an average of
2.5 ppbv, which is higher than the average values of 0.6
(Rappenglück et al., 2013), 1.5 (Hou et al., 2016),
and 1.0 ppbv (Huang et al., 2017) in previous urban studies. The diurnal
variations of HONO during the measurement were similar in the three periods,
as shown in Figs. 3 and 4. The diurnal variations of HONO, NO, NO2,
O3, HONO/NO2, and HONO/NOx are illustrated in Fig. 4. The
error bars of Fig. 4 were placed separately in the tables of the
Supplement (Table S2). After sunset, the HONO concentrations in CD,
PD, and SPD periods began to accumulate due to the attenuation of solar radiation
and the stabilization of the boundary layer (Cui et al., 2018). The
maximum values of 1.7, 4.1, and 6.9 ppbv were reached in the morning
(08:00–10:00 LT) in CD, PD, and SPD periods, respectively. After 10:00 LT, the HONO
concentration decreased because of the increased solubility and rapid
photolysis, which remained at a low level before sunset (14:00–16:00 LT). The NO
concentration decreased rapidly in the forenoon and remained low in the
afternoon. After sunset, the concentrations of NO and NO2 began to
increase and remained at a higher level than during the daytime. Furthermore, the
diurnal variation of NO in the CDs period was similar to that of NO2.
The peak was reached at around 09:00 LT due to vehicle emissions in the
morning rush hours, and the lowest value was observed at around 16:00 LT.
After 18:00 LT, the boundary layer height decreased in the evening rush
hours, resulting in an increase in NO and NO2 concentrations
(Hendrick et al., 2014). O3 showed a diurnal
cycle and had maximum values in CD, PD, and SPD periods in the afternoon.
The HONO/NO2 ratio is commonly used to estimate the formation of HONO
in NO2 transformation (Wang et al., 2013). Compared to
HONO formation, NO2 transformation is less affected by the migration of
atmospheric air mass during atmospheric migration
(Li et al., 2012). The HONO/NO2 ratio
in the CDs period began to increase after sunset and reached its peak at
night. Then, it decreased in the morning as a result of the enhancement of
NO2 emissions and photolysis of HONO. However, the mean value of
HONO/NO2 in PD and SPD periods gradually increased from the nighttime level and
eventually reached the maximum values of 14.3 % and 18.9 % at 09:00 and
10:00 LT, respectively. The average HONO/NOx ratio (4.9 %) was more
than twice the assumed globally averaged value (2.0 %; Elshorbany et al., 2014). This result indicates that the
strength of the heterogeneous reaction increased slightly with the
exacerbation of pollution. The HONO/NO2 ratio showed a diurnal cycle
with a low level in the afternoon and a high level after sunset due to the
heterogeneous reaction of NO2 on the ground and aerosol surfaces
(Su et al., 2008b). For comparison, the daytime and nighttime
HONO, HONO/NO2, and HONO/NOx mean values in other cities around
the world are listed in Table 2. The values of HONO, HONO/NO2, and
HONO/NOx in Zhengzhou are relatively higher than those in other parts
of the world. The reason for this phenomenon is that Zhengzhou is a
high-NOx area that provides HONO with abundant precursors (NO2
and NO) in winter (Kim et al., 2015).
Diurnal variations of HONO during the measurement.
Diurnal variations of HONO, NO, NO2, O3, HONO/NO2,
and HONO/NOx. The blue points and lines represent the CDs period; the
black points and lines represent the PDs period; and the red points and lines
represent the SPDs period.
Comparisons of the daytime and nighttime HONO level, HONO/NO2, and HONO/NOx mean values in Zhengzhou and other sites around the world.
Date (site)InstrumentHONO HONO/NO2HONO/NOxReference(ppbv) (%) (%) DayNightN/DDayNightDayNightOctober–November 2014LOPAP (long path0.91.82.02.64.61.72.2Tong et al. (2015)(Beijing, urban)absorption photometer)February–March 2014LOPAP1.82.11.23.84.32.52.5Hou et al. (2016)(Beijing, urban)(Severe haze) 0.50.91.87.83.05.12.4(Clean) July 2006LOPAP0.20.94.51.02.54.34.5Li et al. (2012)(Guangzhou, rural)July 2014–August 2015LOPAP0.51.63.23.36.2Huang et al. (2017)(Xi'an, urban)August 2010–June 2012Active DOAS0.81.11.44.24.5Wang et al. (2013)(Shanghai, urban)July 2009Wet chemical derivatization0.10.22.03.32.5Michoud et al. (2014)(Paris, urban)technique HPLC/UV–VISdetectionJanuary 2019AIM2.22.81.36.88.54.45.5This studyNocturnal HONO sources and formationHomogeneous reaction of NO and OH
The homogeneous reaction of NO and OH (reactions R2 and R3) is the main pathway of
HONO formation in the gas phase. Spataro et al. (2013) found that the formation mechanism leads to an increase in HONO in
high-pollution areas and an increase in NO at night. POH+NOnet can be understood as the net
hourly HONO production amount of the homogeneous reaction and is calculated as follows:
POH+NOnet=kOH+NO[OH][NO]-kOH+HONO[OH][HONO].
At T=298 K and P=101 kPa, the rate constants of kOH+NO and
kOH+HONO are 9.8×10-12 and 6.0×10-12 cm3 molec.-1 s-1, respectively (Atkinson et al., 2004;
Sander et al., 2003). [OH] is the concentration of ⚫OH that was
not measured during the campaign. Tan et al. (2018) found that, during the field measurement, the average concentration of ⚫OH in
Beijing at nighttime was about 2.5×105 molec. cm-3.
Moreover, the same ⚫OH concentration was also used to calculate
the homogeneous reaction of HONO in the recent research of Beijing
(Zhang et al., 2019), Shanghai (Cui et al., 2018), and Xi'an (Huang
et al., 2017). Nighttime OH concentration increased as the latitude
decreases ranged from 3 to 6×105 molec. cm-3
(Lelieveld et al., 2016). Zhengzhou has a lower latitude than
Beijing, so the concentration of OH used in this study is 2.5×105 molec. cm-3. POH+NOnet
primarily depends on the concentrations of NO and HONO because the values of
kOH+NO and kOH+HONO are close. Figure 5 shows the nocturnal
variations of POH+NOnet, NO, and HONO
during CD, PD, and SPD periods. The uncertainties of
POH+NOnet, NO, and HONO in Fig. 5 are shown in Table S3. When the NO levels were high, the
variations of POH+NOnet followed those of
NO during the three periods (Atkinson et al.,
2004). The mean value of POH+NOnet was
0.33 ppbv h-1, and the specific values in CD, PD, and SPD periods were
0.13, 0.26, and 0.56 ppbv h-1, respectively. We assumed ±50 %
⚫OH values to estimate the uncertainty of
POH+NOnet. The ⚫OH values of
1.25×105 and 3.75×105 molec. cm-3 were
calculated for the POH+NOnet values of 0.16
and 0.49 ppbv h-1.
Nocturnal variations of
POH+NOnet,
HONO, and NO during CD, PD, and SPD periods.
POH+NOnet varied from 0.01 to 0.47 ppbv h-1 during the CDs period. The mean value of
POH+NOnet increased before midnight,
decreased after midnight, and increased slightly at 03:00 LT. In the PDs period,
POH+NOnet ranged from 0.07 to 0.44 ppbv h-1. The situation was similar to that of the CDs period, except that
the value remained almost constant. In addition, the contribution of HONO
from homogeneous reactions during the SPDs period was larger than those in the
CD and PD periods, and the level of
POH+NOnet, with an average value of 0.56 ppbv h-1, was lower than the value in a previous study (2.18 ppbv h-1 in Beijing; Tong et al., 2015). From 19:00 to 03:00 LT, the mean value of POH+NOnet increased
from 0.15 to 0.9 ppbv h-1. HONO increased from 2.84 to 4.59 ppbv and
subsequently decreased to 4.43 ppbv. By integrating
POH+NOnet during the 8 h period, the
homogeneous reaction can provide an accumulated HONO formation of at least
3.36 ppbv (i.e., 0.15+0.20+0.25+0.25+0.35+0.56+0.7+0.9 ppbv). However, the mean accumulation value of measured HONO in this
nighttime period was merely 1.59 ppbv. With the increase in pollution levels,
the HONO accumulation period at nighttime increased. This result indicates
that, first, the homogeneous reaction of OH+NO is sufficient to augment
HONO in the first half of the night, although NO2 transformation and
other sources may still exist. When the concentration of NO is relatively
high, the net production generated by OH+NO may be the leading factor
of the increase in HONO at night (Tong et al., 2015). Second, the
hourly level of HONO abatement pathways, except OH+HONO, should be at
least 0.22 ppbv h-1 (i.e., 3.36–1.59 ppbv (8 h)-1). This phenomenon may
arise because the dry deposition on ground surfaces can be the main HONO
removal pathway at night, which is similar to a previous study
(Li et al., 2012).
Direct emission
At present, no HONO emission inventory or emission factor database is available for Zhengzhou. As a result, estimating any HONO from direct
emissions is difficult. In the current study, directly emitted HONO could
have been generated by vehicle exhaust emissions and biomass combustion because the site is close to the West Fourth Ring expressway of Zhengzhou and Lian Huo Expressway in the north. Hence, only night data (17:00–06:00 LT) were considered to avoid the problem of instant photolysis of directly
emitted HONO. In a previous study, the HONO/NOx ratio from tunnel
measurement was set to 0.65 % to estimate an upper limit of HONO emitted
by traffic near the site (Kurtenbach et al., 2001). The minimum value of
HONO/NOx in the SPDs period in the current work was 1.5 %, which is
slightly higher than the value measured in the abovementioned study.
HONO emitted directly at night was not transformed immediately. The HONO
concentrations corrected by direct emissions are given as follows:
[HONO]correct=[HONO]-[HONO]emission=[HONO]-0.0065×[NOx],
where [HONO]emission, [NOx], and 0.0065 are the direct HONO emissions concentration, NOx concentration, and HONO/NO2 direct emissions
ratio, respectively. The direct emissions contribution was estimated by
comparing the direct emission HONO with the observed HONO. The ranges of
HONOemission/HONO in CD, PD, and SPD periods were 2 %–52 %, 6 %–34 %,
and 2 %–41 %, respectively, and the mean values were 17 %, 16 %, and 16 %,
respectively. The frequency distribution of the HONOemission/HONO ratio
at nighttime is shown in Fig. 6. For this upper-limit estimation, the
frequency distribution of HONOemission/HONO (less than 20 %) was
approximately 77 %. Hence, direct emissions may not be the main reason for
the high growth of HONO levels. Compared to the direct emissions of other
sites, the emissions of the measurement site accounted for a lower proportion – possibly because the site is on the campus and relatively far from the highway.
Percentage distribution of the nighttime HONOemission/HONO.
(The dotted line represents the average of HONOemission/HONO.)
Heterogeneous conversion of NO2 to HONO
NO2 is an important precursor for HONO formation. In addition, recent
field measurements in many urban locations have shown that a positive
correlation exists between HONO and NO2 (Cui et al., 2018; Hao et
al., 2006; Huang et al., 2017; Zhang et al., 2019), which suggests that they have a
common source. Moreover, Acker et al. (2005) reported that
different meteorological conditions may lead to significant differences in
the relationship between the source and receptor, and these differences lead
to various types of correlations. During the measurement period, the
HONO/NO2 ratio varied between 1.3 % and 59.0 %, with an average of
7.6 %, which is slightly higher than the averaged value of 6.2 % in a
previous study (Cui et al., 2018). The HONO/NO2 ratio calculated in
this work is much larger than the ratio calculated for direct emissions (<1 %; Kurtenbach et al., 2001), suggesting that heterogeneous reactions
may be a more important pathway for HONO production than direct emissions.
With regard to the heterogeneous conversion of NO2, several studies
(An et al., 2012; Shen and Zhang, 2013) reported that the surface of
soot particles is the medium of NO2 conversion. The contribution of
soot surface to HONO production is usually much lower than expected because
the uptake efficiency of NO2 decreases with the prolonged reaction time
caused by surface deactivation. The aerosol surface is an important medium
for the heterogeneous transformation from NO2 to HONO
(Liu et al., 2014). The mass concentration of aerosols was
used as an alternative to identify the influence of aerosols in this study
because the surface density of aerosols could not be obtained.
Nighttime correlation studies between PM2.5 and HONO/NO2;
PM2.5 and HONO; CO and HONO; and RH and HONO/NO2 during the entire
measurement period – including the CD, PD, and SPD periods. The blue lines represent the full
measurement period; the light blue points represent the CDs period; the black points represent the PDs period; and the red points represent the SPDs period.
The correlations between PM2.5 and the HONO/NO2 ratio in CD, PD, and
SPD periods are shown in Fig. 7. With the exacerbation of the PM2.5
level, the average value of HONO/NO2 gradually increased, indicating
that the aerosol surface occupied an important position in the heterogeneous
transformation. A comparison of HONO/NO2 and HONO with PM2.5
showed that the correlation between HONO/NO2 and PM2.5 (R2=0.23) was weaker than that between HONO and PM2.5 (R2=0.55) during the entire period. The main source of HONO could not have been the
transformation of NO2. Notably, the HONO correlation in the PDs period
was significantly stronger than that of the other two periods. This result
proves that HONO-related reactions occurred more frequently during this
period. The fair correlation between HONO and PM2.5 may pinpoint the
mainly anthropogenic origins of these two pollutants with the high direct or
indirect contribution of combustion sources. The reason for the increased
HONO during the heavy pollution period could be due to the comparatively high
loading and large particle surface (Cui et al., 2018). Similar phenomena
have been observed in a correlation study on CO and HONO in which CO was used
as a tracer for traffic-induced emissions and tested by considering the
correlation between HONO and CO over an identical time interval
(Qin et al., 2009). The correlation coefficient between HONO and
CO was relatively moderate (R2=0.43), indicating that HONO and CO
could come from the same source of emissions. Generally speaking, CO and NO
are mainly related to combustion processes such as vehicle emissions and fossil
fuel and biomass combustion (Tong et al.,
2016). Thus, fossil fuel and biomass combustion may contribute to HONO
production, but they cannot be measured directly.
The absorbed water influences the heterogeneous formation (Stutz
et al., 2004). The influence of RH on the heterogeneous conversion is shown
in Fig. 7d. When RH was less, the HONO/NO2 ratio slowly increased.
When RH was increased, the HONO/NO2 ratio began to increase rapidly
with RH. The HONO/NO2 ratio decreased when RH reached a certain high
level. Similar variation patterns have been observed in previous studies
(Huang et al., 2017; Qin et al., 2009; Tong et al., 2015). Surface
adsorbed water functions not only as the source but also as the sink of HONO by
affecting the hydrolysis of NO2 and the sedimentation of HONO to
generate HONO (Ammann et al., 1998). When RH ranged at
the middle level, the heterogeneous conversion of NO2 to HONO was more
significant than that of the deposition. This phenomenon confirms that RH
improved the conversion efficiency (Stutz et al., 2004).
However, the surface reached saturation when RH reached a certain high
level. The excess water restricted NO2 transformation
(Wojtal et al., 2011). The absorption and dissolution of HONO by
the saturated surface water layer caused the HONO/NO2 ratio to decrease
drastically.
Nocturnal variations of HONOcorrect, NO2, and
HONOcorrect/NO2 in CD, PD, and SPD periods.
The correlation between HONOcorrect and NO2 at nighttime is shown
in Fig. S1. HONOcorrect was used in the calculation to exclude the
influence of direct emissions on NO2 conversion. The nocturnal
variations of HONOcorrect, NO2, and HONOcorrect/NO2
ratios in the CD, PD, and SPD periods are presented in Fig. 8. The
uncertainties of HONOcorrect, NO2, and HONOcorrect/NO2
ratios in Fig. 8 are shown in Table S4. In general, the
HONOcorrect/NO2 ratio reached its maximum at or before midnight
but decreased after midnight. In the PD and SPD periods, HONO was generated
by heterogeneous reaction (R4), and NO2 decreased after midnight. The
production of HONO was equal to its loss (mainly night deposition), and the HONO
concentration reached a relative balance. The weak correlation between
nighttime HONO/NO2 and PM2.5 can be reasonably explained by the
stable HONOcorrect/NO2 ratio after midnight (Qin et
al., 2009). A previous study (Xu et al., 2015) found that a
low HONOcorrect in the first half of the night (19:00–00:00 LT)
indicates the important contribution of automobile exhaust emissions, and a
low HONOcorrect in the second half of the night means heterogeneous
reactions dominate. Therefore, the heterogeneous reaction conversion rate of
HONO was calculated in the current study by using the data of
HONOcorrect.
The conversion rate of HONO (CHONO) is usually used as an indicator to
test the efficiency of NO2 heterogeneous reactions. Total
HONOcorrect was assumed to be generated by the heterogeneous
transformation of NO2. The formula for the conversion rate of NO2
(CHONO) is as follows (Su et al., 2008a; Xu et al., 2015):
CHONO=[HONOcorrect]t2-[HONOcorrect]t1(t2-t1)[NO2],
where [NO2] is the average concentration of NO2 within the t2-t1
time interval (1 h). In this study, the averaged conversion rate of NO2
was 1.02×10-2 h-1. The mean values of CHONO in
the CD, PD, and SPD periods were 0.72×10-2, 0.64×10-2, and 1.54×10-2 h-1, respectively. The averaged
conversion rates in this study were 0.58×10-2 and
1.46×10-2 h-1 higher than those of Beijing I
(polluted) and II (heavily polluted) periods, respectively. The increase in
the conversion rate demonstrates that NO2 had high reaction efficiency
through the process from NO2 to HONO in the aggravation of pollution,
which could have led to the high utilization efficiency of the aerosol
surface. The exact uptake coefficients of NO2 on the ground and aerosol
surfaces are variable and should be different (Harrison and
Collins, 1998). The present analysis simplified this process by treating the
ground and aerosol surfaces in the same way. The uptake coefficient is mainly
dependent on the surface characteristics, e.g., surface type and moisture
(Lu et al., 2018).
The average profiles of JHONO and JO1D
concentrations during the daytime, and the production and loss rate of the
daytime HONO in CD, PD, and SPD periods.
Daytime HONO budget
The expression of dHONO/dt represents the observed variations of hourly
HONO concentrations, for which we can use ΔHONO/Δt
in the following way instead:
4dHONO/dt=sources-sinks=Punknown+POH+NO+Pemi+Phet-LOH+HONO+Lphoto,5POH+NO=kOH+NO[OH][NO],6LOH+HONO=kOH+HONO[OH][HONO].
The dHONO/dt calculated from the measurements was small and evenly
distributed at around zero (Li et al., 2012).
Punknown is the production rate by an unknown daytime HONO source.
POH+NO is the rate of reaction of NO and OH. Pemi represents the
direct emission rate of HONO from combustion processes. The daytime HONO budget was analyzed with Eq. (4) by studying the source and reduction (Su et al., 2008b). The heterogeneous transformation mechanism was
assumed to be the same for day and night. Therefore, the daytime
heterogeneous productivity (Phet=CHONO×[NO2])
was calculated with the nighttime mean values of CHONO in different
periods. LOH+HONO is the rate of the reaction between OH and HONO (reaction R3).
The calculation formulas of POH+NO and LOH+HONO have been
provided in Sect. 3.2.1. Upon sunlight irradiation, ⚫OH and NO
were formed as reaction R1. Lphoto represents the photolysis loss rate of HONO
(Lphoto=JHONO×[HONO]). The photolysis frequency
and ⚫OH concentration could not be directly measured in this
study. Therefore, the tropospheric ultraviolet and visible (TUV) transfer
model of the National Center for Atmospheric Research
(http://cprm.acom.ucar.edu/Models/TUV/Interactive_TUV/, last access: 2 October 2019; Hou et al., 2016) was used to
calculate the JHONO value. The JHONO values obtained this way
were assumed for clear-sky days without clouds. O3 column density was measured by the Ozone Monitoring
Instrument (OMI, https://ozonewatch.gsfc.nasa.gov/data/omi/Y2019/, last access: 30 August 2019). The O3 column
density ranges from 292 to 306 DU during the entire period. Because the experimental
site is situated in an urban region, the surface albedo is considered to be
0.13 (Sailor, 1995). The ground elevation and the measurement
altitude are 168 and 188 m respectively. The concentration of OH radicals
was calculated with the formulas of NO2, O3, and
JO1D in the Supplement (Rohrer and
Berresheim, 2006). Aerosol effects were considered by using aerosol optical
thickness (AOD), single scattering albedo (SSA), and the Ångström exponent as
inputs in the TUV model. Typical AOD, SSA, and Ångström exponent values of
1.32, 0.9, and 1.3, respectively, were adopted for the PD and SPD periods.
In the CDs period, the respective values were 0.66, 0.89, and 1.07 (Che et
al., 2015; Cui et al., 2018; Hou et al., 2016). We wanted to study the production and loss rate of HONO under the same output conditions from the TUV model in the PD and SPD
periods; however, the impact of different pollution levels changed the daytime
budget. Hence, the average profiles of JHONO and JO1D
concentrations in the CD, PD, and SPD periods are shown in Fig. 9. The mean
values of JHONO and ⚫OH concentration at noon in the CD, PD,
and SPD periods were 5.93×10-4, 3.79×10-4, and
3.79×10-4 and 4.10×106,
2.93×106, and 3.76×106 molec. cm-3,
respectively. The results of the calculated OH radicals ranged (0.58–11.49) ×106 molec. cm-3, and the mean value
was 3.57×106 molec. cm-3 at noon in Zhengzhou.
Each production and loss rate of daytime HONO during CD, PD, and SPD periods
is illustrated in Fig. 9m, together with dHONO/dt. Punknown was at a high
level before midday. Punknown approached 0 ppbv h-1 after midday.
In the CD, PD, and SPD periods, the mean values of Punknown were 0.26,
0.40, and 1.83 ppbv h-1, respectively; the mean values of POH+NO
were 1.14, 2.07, and 4.03 ppbv h-1, respectively; the mean values of
Pemi were 0.17, 0.30, and 0.43 ppbv h-1, respectively; and the
mean values of Phet were 0.14, 0.18, and 0.55 ppbv h-1,
respectively. The midday time Punknown (1.83 ppbv h-1) calculated
in Zhengzhou during the winter haze pollution period was close to the result
obtained from Beijing's urban area (Hou et al., 2016; 1.85 ppbv h-1). The Punknown contribution to daytime HONO sources in CD, PD,
and SPD periods accounted for 15 %, 14 %, and 28 % of the HONO production rate
(Punknown+POH+NO+Pemi+Phet),
respectively. Previous studies (Spataro et al., 2013; Yang et al., 2014)
showed that meteorological conditions, such as solar radiation and WS,
can affect unknown sources. The low Punknown contribution of daytime
HONO concentration may be related to the low solar radiation and low wind
speed during severe pollution. The concentration of NO has a great influence
on POH+NO, so the homogeneous reaction is still an important pathway of
HONO production during the daytime. In addition to the photolysis of HONO
and the homogeneous reaction of HONO and OH, one, or more, important sink
might exist to control the variation between the sources and sinks of the
daytime HONO during complex contamination. However, further research is
needed to analyze the unknown sources of daytime HONO.
Conclusions
Ambient HONO measurement, using AIM with other atmospheric pollutants and
meteorological parameters, was conducted in the CPER. The HONO concentrations
during the entire measurement varied from 0.2 to 14.8 ppbv, with an average
of 2.5 ppbv. The HONO concentrations in the CD, PD, and SPD periods were
1.1, 2.3, and 3.7 ppbv, respectively, and the HONO/NO2 ratios were 4.7 %,
7.1 %, and 9.4 %, respectively. HONO concentration was a combined action of
direct emissions and heterogeneous reaction, and the contributions of these two
were higher than those of the homogeneous reactions in the first half of the
night. However, the proportion of homogenization gradually increased in the
second half of the night due to the steady increase in NO concentration. The
hourly level of other HONO abatement pathways, aside from OH+HONO, should
be at least 0.22 ppbv h-1 in the SPDs period. The sum of the frequency
distributions of the HONOemission/HONO ratio (less than 20 %) was
approximately 77 %, indicating that the direct emission of HONO was not
the main source of the observed HONO level at night. The mean values of
HONOemission/HONO in the CD, PD, and SPD periods were 17 %, 16 %, and
16 %, respectively. This phenomenon means that the policy of restricting
motor vehicles, published by the local government in January 2019, had a good
effect on decreasing HONO emissions. In addition, when RH increased at the
middle level, the heterogeneous HONO production increased, but it decreased
when RH increased further due to the effect of surface water. The
contribution of the three sources varied with different pollution levels.
The mean values of CHONO in the CD, PD, and SPD periods were
0.72×10-2, 0.64×10-2, and 1.54×10-2 h-1, respectively. In the SPDs period at nighttime, the
heterogeneous conversion of NO2 appeared to be unimportant.
Furthermore, the net production generated by homogeneous reaction may be the
leading factor for the increase in HONO under high-NOx conditions
(i.e., the concentration of NO was relatively higher than that of NO2)
at nighttime. The mean values of POH+NOnet
in the CD, PD, and SPD periods were 0.13, 0.26, and 0.56 ppbv h-1,
respectively. Daytime HONO budget analysis showed that the mean values of
Punknown in the CD, PD, and SPD periods were 0.26, 0.40, and 1.83 ppbv h-1, respectively. Although the values of POH+NO had high
uncertainty because of the variation of NO concentrations, POH+NO
contributed the most to HONO production during the daytime. After analysis, CHONO, POH+NOnet, and
Punknown in the SPDs period were larger than those in the other periods,
indicating that HONO participated in many reactions.
Data availability
All the data used in this paper are available from the corresponding author upon request (jiangn@zzu.edu.cn).
The supplement related to this article is available online at: https://doi.org/10.5194/acp-20-7087-2020-supplement.
Author contributions
NJ, RZ, and, SL conceived and designed the study. QH analyzed the data and wrote the paper. LY performed aerosol sampling and data analyses.
Competing interests
The authors declare that they have no conflict of interest.
Financial support
This research has been supported by the National Natural Science Foundation of China (grant nos. 51808510 and 51778587), the National Key Research and Development Program of China (grant no. 2017YFC0212400), the Natural Science Foundation of the Henan Province of China (grant no. 162300410255), and the National Research Program for Key Issues in Air Pollution Control (grant no. DQGG0107).
Review statement
This paper was edited by Eliza Harris and reviewed by three anonymous referees.
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