PM2.5, particulate matter with a diameter of 2.5 µm or less,
is one of the major components of air pollution in eastern China. In the
past few years, China's government has made strong efforts to reduce
PM2.5 pollution. However, another important pollutant (ozone) is becoming
a problem in eastern China. Ozone (O3) is produced by
photochemistry, which requires solar radiation for the formation of O3.
Under heavy PM2.5 pollution, solar radiation is often depressed,
and the photochemical production of O3 is prohibited. This study shows
that during late spring and early fall in eastern China, under heavy
PM2.5 pollution, there was often strong O3 photochemical
production, causing a co-occurrence of high PM2.5 and O3
concentrations. This co-occurrence of high PM2.5 and O3 is
unusual and is the main focus of this study. Recent measurements show that
there were often high HONO surface concentrations in major Chinese megacities, especially during daytime, with maximum concentrations ranging from
0.5 to 2 ppbv. It is also interesting to note that high HONO
concentrations occurred during high aerosol concentration periods,
suggesting that there were additional HONO surface sources in eastern China.
Under high daytime HONO concentrations, HONO can be photodissociated to
OH radicals, which enhance the photochemical production of O3. In
order to study the above scientific issues, a radiative transfer model (TUV;
tropospheric ultraviolet–visible) is used in this study, and a chemical
steady-state model is established to calculate OH radical concentrations.
The calculations show that by including the OH production of
photodissociated HONO, the calculated OH concentrations are
significantly higher than the values without including this production. For
example, by including HONO production, the maximum OH concentration under
high aerosol conditions (AOD = 2.5) is similar to the value under low
aerosol conditions (AOD = 0.25) in the no-HONO case. This result suggests
that even under high aerosol conditions, the chemical oxidizing process
for O3 production can occur, which explains the co-occurrence of high
PM2.5 and high O3 in late spring and early fall in
eastern China. However, the O3 concentrations were not significantly
affected by the appearance of HONO in winter. This study shows that the
seasonal variation of solar radiation plays important roles for controlling
the OH production in winter. Because solar radiation is at a very low
level in winter, adding the photolysis of HONO has a smaller effect in winter
than in other seasons, and OH remains at low values by including the HONO
production term. This study provides some important scientific insight to
better understand O3 pollution in eastern China.
Introduction
Currently, China is undergoing rapid economic development, resulting in a
higher demand for energy and greater use of fossil fuels. As a result,
high emissions of pollutants produce heavy pollution in the megacities of
eastern China, such as Beijing and Shanghai. For example, in the city of
Shanghai (a large megacity in China), urban and economic
developments of the city are very rapid. During 1990 to 2015, the population
increased from 13.3 to 24.1 million. The number of automobiles increased
from 0.2 million (1993) to 2.0 million (2011). The rapidly growing population
and energy usage caused a rapid increase in the emissions of pollutants,
leading to severe air pollution problems in these megacities (Zhang et al.,
2006; Geng et al., 2007; Deng et al., 2008).
Measurements such as satellite observations have revealed much higher
aerosol pollution in eastern China than in the eastern US (Tie et al., 2006).
High aerosol pollution causes a wide range of environmental
consequences. Jia et al. (2019) studied anthropogenic aerosol pollution over
the eastern slope of the Tibetan Plateau, and Zhu et al. (2018) studied the
impact of smoke aerosols from Russian forest fires on the air pollution over
Asia. According to a study by Tie et al. (2009a), exposure to extremely high
particle concentrations leads to a great increase in lung cancer cases. High
PM (particular matter) concentrations also significantly reduce the range of
visibility in China's megacities (Deng et al., 2008). According to a recent
study, high aerosol pollution causes important effects on crop (rice
and wheat) production in eastern China (Tie et al., 2016).
The geographic locations of the measurement sites in Beijing, from
which the measured concentrations of PM2.5 and O3 are used in the
analysis.
In the troposphere, ozone formation results from a complicated chemical
process and requires ozone precursors, such as VOCs (volatile organic
carbons) and NOx=NO+NO2 (nitrogen oxides) (Sillman,
1995). With the increase in industrial activity and the number of automobiles, the
precursors of ozone (O3) and the global budget of oxidization are also
significantly increased (J. P. Huang et al., 2017, 2018). As a
result, O3 pollution is becoming a serious pollution problem in Shanghai and
other Chinese megacities (Geng et al., 2010; Tie et al., 2009b, 2015).
The effects of the O3 production rate can be characterized as either
NOx-sensitive or VOC-sensitive conditions. For city areas, O3
production is generally VOC-sensitive, while in remote areas, O3
production is generally NOx-sensitive in eastern China (Sillman, 1995; Zhang
et al., 2003; Lei et al., 2004; Tie et al., 2013). Thus, better
understanding the trends of O3 precursors (VOCs, NOx) is
important to determine the O3 trends in Shanghai (as well as many
large cities in China).
The daily averaged concentrations of PM2.5 and O3 in the
Beijing region in 2015. The concentrations are averaged over all sites shown
in Fig. 1. The blue lines represent the PM2.5 concentrations (µg m-3), and the red bars represent the O3 concentrations (µg m-3). The rectangles show some typical events during winter (green),
spring and fall (orange), and summer (red).
The correlation between O3 and PM2.5 concentrations during
winter (a) and from late spring to early fall (b).
During winter, O3 concentrations were strong anticorrelated with
PM2.5 concentrations. From late spring to early fall, O3
concentrations were correlated with PM2.5 concentrations.
In the past few years, China's government has made strong efforts to reduce
PM2.5 pollution. However, another important pollutant (O3)
is becoming a problem in eastern China. Several studies regarding
O3 formation have been previously conducted in Shanghai. For example, Geng et
al. (2007, 2008) studied the relationship between O3 precursors (NOx and
VOCs) for ozone formation in Shanghai. Tie et al. (2009) studied the
short-term variability of O3 in Shanghai. Their study suggested that in
addition to ozone precursors, meteorological conditions, such as
regional transport, also have strong impacts on ozone concentrations.
During September 2009, a major field experiment (MIRAGE-Shanghai) was
conducted in Shanghai, and multiple chemical species were measured during
the experiment. The summary of the measurements by Tie et al. (2013) suggests
that ozone formation in Shanghai is under VOC-sensitive conditions.
However, if the emission ratio of NOx/VOCs is reduced to a lower value
(0.1–0.2), the ozone formation in Shanghai will switch from VOC-sensitive
conditions to NOx-sensitive conditions.
The diurnal variations of PM2.5 (blue line), O3 (red
line), and NO2 (green line) during a fall period (from 5 to 6 October 2015). It shows that under high PM2.5 conditions, there was a strong
O3 diurnal variation.
The cloud conditions during the period of the case study (between 5 and 6 October 2015) in the Beijing region. Bright white shows the cloud
cover, and grey–white shows the haze cover. The Beijing region was
under heavy haze conditions during the period. The figure is download
from https://worldview.earthdata.nasa.gov (last access: 15 July 2019), with additions.
Despite the fact that some progress has been made for ozone formation in megacities in China, there is still a lack of studies on ozone development in large
cities of China. For example, this study shows that during late spring and
early fall in eastern China, under heavy PM2.5 pollution, there was
often strong O3 chemical production, causing the co-occurrence of high
PM2.5 and O3 concentrations. Under heavy aerosol conditions,
solar radiation is depressed, significantly reducing the photochemical
production of O3. This co-occurrence of high PM2.5 and O3 is
unusual and is the focus of this study. He and Carmichael (1999) suggest
that aerosol particles can enhance the scattering of solar radiation,
enhancing the flux density inside the boundary layer. Recent measurements
also show that there were often high HONO concentrations in major Chinese
megacities, especially during daytime, with maximum concentrations ranging
from 0.5 to 2 ppbv (Huang et al., 2017). Zhang et al. (2016) suggest that
there are several potential HONO sources, including surface emissions and
conversion of NO2 at the ocean surface, and adding these sources
can improve the calculated HONO concentrations. It is also interesting to
note that high HONO surface concentrations occurred during high
aerosol concentration periods, suggesting that there are additional HONO
surface sources in eastern China. Under high daytime HONO
concentrations, HONO can be photodissociated to OH radicals, which
enhance the photochemical production of O3.
The measured solar radiation (W m-2) from 3 to 9 October 2015
in Beijing. (a) Hourly values and (b) daytime averaged values.
The paper is organized as follows: in Sect. 2, we describe the measurement
of O3 and PM2.5. In Sect. 3, we describe the calculation of
the photodissociation rate of HONO, a steady-state model for the calculation
of OH, and the causes of high O3 production under heavy aerosol
conditions. Section 4 shows a brief conclusion of the results.
Measurements of O3 and PM2.5
There are long-term measurements in eastern China by the Chinese Environment
Protection Agency (CEPA) for monitoring the air quality in China. In eastern
China, especially in the capital city of China (Beijing), there is often
heavy air pollution, particularly fine particular matter (PM2.5 –
the radius of particles being less than 2.5 µm). Figure 1 shows the
measurement sites in Beijing, from which the measured concentrations of
PM2.5 and O3 are used in the analysis. In the region, the air
pollution was very heavy, especially in winter (Long et al., 2016; Tie et
al., 2017). Previous studies suggest that both aerosol and O3
have become major pollutants in the region (Li et al., 2017).
Figure 2 shows the daily averaged concentrations of PM2.5 and O3
in the Beijing region in 2015. The daily averaged concentrations show that
there were strong daily and seasonal variations for the concentrations
of both PM2.5 and O3. Despite the daily variation, the concentrations
of PM2.5 exhibited a strong seasonal variation. For example, there were
very high concentrations during winter, with a maximum of ∼300µg m-3, while in summer, the maximum concentrations were reduced to
∼150µg m-3. The seasonal variability of O3
concentrations were opposite to the PM2.5 concentrations, with lower
concentrations in winter (< 50 µg m-3) and higher
concentrations in summer (> 150 µg m-3). These seasonal
variations of PM2.5 and O3 have been studied by previous authors
(Tie and Cao, 2017; Li et al., 2017). Their results suggest that
high winter PM2.5 concentrations resulted from the combination of
high emissions (heating season in the Beijing region) and poor
meteorological ventilation conditions, such as a lower PBL (planetary boundary
layer) height (Quan et al., 2013; Tie et al., 2015). According to the
photochemical theory of O3 formation, high summer and low winter
O3 concentrations are mainly due to the seasonal variation of solar
radiation (Seinfeld and Pandis, 2006).
Heavy aerosol concentrations play important roles in reducing solar
radiation, causing the reduction of O3 formation (Bian et al., 2007).
As we show in Fig. 3a, during wintertime, the O3
concentrations were strongly anticorrelated with the PM2.5
concentrations, suggesting that the reduction of solar radiation by aerosol
particles has an important impact on the reduction of O3 concentrations.
Figure 3a also shows that the relationship between O3 and
PM2.5 was not linearly related. For example, when the concentrations of
PM2.5 were less than 100 µg m-3, O3 concentrations
rapidly decreased with the increase in PM2.5 concentrations. In
contrast, when the concentrations of PM2.5 were greater than 100 µg m-3, O3 concentrations slowly decreased with the increase in
PM2.5 concentrations. This is consistent with the result of Bian et al. (2007).
The effect of aerosol levels with AOD = 0.25 (black line), AOD = 2.5 (red line), AOD = 3.5 (blue line), and AOD = 4.0 (green line) on the
O3 photolysis calculated by the TUV model in October at
middle latitudes.
It is interesting to note that from late spring to early fall, the
correlation between PM2.5 and O3 concentrations was positive
compared to the negative relationship in winter (see Fig. 3b). This result suggests that O3 production was high during
the heavy haze period, despite the fact that the solar radiation was greatly depressed. In
order to clearly display this unusual event, we illustrate diurnal
variations of PM2.5, O3, and NO2 during a fall period
(from 5 to 6 October 2015). Figure 4 shows that during this period (as a
case study), the PM2.5 concentrations were very high, ranging from 150
to 320 µg m-3. Under such high aerosol conditions, the solar
radiation should be significantly reduced, and O3 photochemical
production would also be reduced. However, the diurnal variation of O3 was
unexpectedly strong, with a high noontime concentration of > 220 µg m-3 and very low nighttime concentration of ∼25µg m-3. This strong diurnal variation was due to photochemical
activity, which suggested that during relatively low solar conditions, the
photochemical activities of O3 production were high. According to the
theory of O3 chemical production, high O3 production is
related to a high oxidant of OH (Seinfeld and Pandis, 2006), which should not
occur during lower solar radiation. This result brings up an important issue
for air pollution control strategies because both PM2.5 and O3
are severe air pollutants in eastern China.
To clearly understand the effect of high aerosol concentrations on solar
radiation, we investigate the meteorological conditions, such as cloud
cover, relation humidity (RH), and solar radiation, during the period of the
case study (see Figs. 5 and 6). Figure 5 shows that the cloud condition was
close to cloud-free, but there was a very heavy aerosol layer
in the Beijing region, suggesting that cloud cover played a minor role in
the reduction of solar radiation. The measured RH values (not shown)
were generally higher than 60 %, with a maximum of 95 % during the
period. As a result, high aerosol concentrations accompanied by high RH
produced important effects on solar radiation. As shown in Fig. 6, the
daytime averaged solar radiation was significantly reduced (about a 40 %
reduction in the 5–6 October period compared with the value of 8 October).
(a) Measured HONO concentrations (ppbv) and PM2.5 and
O3 daily concentrations in Beijing. The upper graph shows the measured
daily concentrations of PM2.5 and O3 as shown in Fig. 2. The
dark red line represents measured HONO in Beijing from 1 to 27 January 2014.
(b) Measured HONO concentrations (ppbv) and PM2.5 and
O3 daily concentrations in Shanghai. The upper graph shows the measured
daily concentrations of PM2.5 and O3 in 2015. The dark red line
was measured in Shanghai from 9 to 18 September 2009. The green line was
calculated by the WRF-Chem model. (c) Measured HONO concentrations (ppbv) and PM2.5 and
O3 daily concentrations in Xi'an. The upper graph shows the measured
daily concentrations of PM2.5 and O3 in 2015. The red line represents
measured HONO in Xi'An from 24 July to 6 August 2015.
Methods
In order to better understand the O3 chemical production that occurred in
heavy aerosol conditions in eastern China, the possible O3 production in
such conditions is discussed. Ozone photochemical production (P[O3]) is
strongly related to the amount of OH radicals (Chameides et al., 1999).
According to the traditional theory, the amount of surface OH radicals is
proportional to the surface solar radiation, which is represented by
[OH]=P[HOx]/L[HOx]*,
where [OH] represents the concentration of hydroxyl radicals
(no. cm-3), where “no.” represents the number of molecules; HOx represents the concentration of HO2+OH
(no. cm-3); P[HOx] represents the photochemical production of HOx
(no. cm-3 s-1); and L[HOx]* (1 s-1) represents the photochemical
destruction of HOx, which is normalized by the concentrations of OH.
The major process for the photochemical production of P[HOx] is through
O3 photolysis and follows the reaction with atmospheric water vapor.
It can be expressed as
PHOx=J1O3/(k1×am)×2.0×k2H2O=P1HOx,
where J1 represents the photolysis of O3+hv→O1D;
k1 represents the reaction rate of O1D+ am →O3P; and
k2 represents the reaction rate of O1D+H2O→ 2OH. As
we can see, this HOx production is proportional to the magnitude of solar
radiation (J1), and J1 is O3 photolysis with solar
radiation. Figure 7 shows the relationship between the values of J1 and
aerosol concentrations in October at middle latitudes calculated by the TUV
model (Madronich and Flocke, 1999). This result suggests that under high
aerosol concentrations (AOD = 2.5), the J1 value is strongly
depressed, resulting in a significant reduction of OH concentrations and
O3 production. For example, the maximum J1 value is about
2.7×10-5 (1 s-1) with lower aerosol values (AOD = 0.25). According to
a previous study, the surface PM2.5 concentrations were generally
smaller than 50 µg m-3 with this AOD value (Tie et al., 2017).
However, when the AOD value increased to 2.5 (the PM2.5 concentrations
are generally > 100 µg m-3), the maximum J1 value
rapidly decreased to about 6×10-6 (1 s-1), which is about a 450 %
reduction compared to the value with AOD = 0.25. This study suggests that
under high PM2.5 concentrations (>100 µg m-3), the
photochemical production of OH (P[HOx]) is rapidly decreased, leading to low
OH concentrations, which cannot initiate the high oxidation of O3
production. As a result, the high O3 production shown in Fig. 4 cannot
be explained. Other sources for O3 oxidation are needed to explain this
result.
Measured HONO (b), PM2.5 concentrations
(c), and O3 concentrations (a) in fall
in Shanghai, illustrating that high HONO concentrations
corresponded to high PM2.5 concentrations.
Recent studies show that HONO concentrations are high in eastern China
(R. J. Huang et al., 2017). Under high solar radiation, the photolysis
rate of HONO is very high, resulting in very low HONO concentrations in
daytime (Seinfeld and Pandis, 2006). These measured high HONO concentrations
are explained by other studies. One of the explanations is that there are
high surface HONO sources during daytime, which produces high HONO
concentrations (R. J. Huang et al., 2017). Zhang et al. (2016) suggest that there
are several potential HONO sources, including surface emissions and conversion
of NO2 at the ocean surface. Zhang et al. (2016) parameterized
these potential HONO sources in the WRF-Chem model, and the calculated HONO
concentrations are increased in the WRF-Chem model.
The WRF-Chem model is based on the version developed by Grell
et al. (2015) and is improved mainly by Tie et al. (2017) and Li et al. (2011). The chemical mechanism chosen in this version of WRF-Chem is the
RADM2 (Regional Acid Deposition Model, version 2) gas-phase chemical
mechanism. For the calculation of HONO, only the gas-phase chemistry of
OH+NO is included to calculate HONO concentrations. As shown in Fig. 8,
the calculated HONO concentrations are significantly smaller than the
measured HONO values in eastern China, suggesting that in addition to the
gas reaction, there are missing HONO sources (surface sources or others).
Because these missing sources are not fully understood and large uncertainty
remains, in the following calculation, we compare the OH concentrations
due to both calculated HONO (without the missing sources) and measured
HONO concentrations to illustrate the importance of these missing sources
for the production of OH radicals and to suggest that further study is needed to
better understand the missing sources; this is an urgent scientific issue.
The calculated OH production P(HOx) (no. cm-3 s-1) by using the
model-calculated HONO (low concentrations) (a) and by using
the measured HONO (high concentrations) (b). The blue bars
represent the calculation of the P1 term, and the red bars represent the
calculation of the P2 term (OH production from HONO).
The calculated OH concentrations (no. cm-3) with (a)
and without (b) HONO production of OH under different aerosol
levels. Dark red (AOD = 0.25), red (AOD = 1.0), blue (AOD = 2.5), green (AOD = 3.5), and beige
(AOD = 4.0).
Figure 8 shows the measured HONO concentrations in three large cities in
China (Shanghai, Xi'an, and Beijing) during fall and winter. It also shows
the corresponding PM2.5 and O3 in the three cities (i.e., Fig. 8a for
Beijing, Fig. 8b for Shanghai, and Fig. 8c for Xi'an). It shows that the
measured HONO concentrations were high, ranging from smaller than parts per billion measurements to a few parts per billion by volume,
with higher values during morning and lower values in daytime. Co-occurrences of high PM2.5 and O3 happened in the three cities. As a
result, we think that the high HONO is a common event in large cities in
eastern China, especially in daytime. This high HONO is also measured by
previous studies (Zhang et al., 2016; Huang et al., 2017). In this study, we
make an assumption that the co-occurrence between O3 and PM2.5
occurred under high HONO concentrations. We note that using this assumption
may result in some uncertainties in estimating the effect of HONO on OH. For
example, using the measured HONO in Xi'an and Beijing could produce 1–2 times higher OH production by the photolysis of HONO than the result by using
the data from Shanghai. In this case, we use the measured HONO from Shanghai
to avoid overestimating the HONO effect, which can be considered a
low-limit estimation.
It is also interesting to note that high HONO concentrations
occurred during high aerosol concentration periods. Figure 9 illustrates
that when the PM2.5 concentrations increased to 70–80 µg m-3,
the HONO concentrations were enhanced to 1.4–18 ppbv during September in
Shanghai. These measured HONO concentrations were significantly higher
than the calculated concentrations (shown in Fig. 8), suggesting that some
additional sources of HONO are needed. This result is consistent with
HONO measurements in other Chinese cities (Huang et al., 2017).
The effect of cloud cover on the photolysis rate of HONO (J[HONO]).
The blue, red, and green lines represent cloud water vapor of 0 g m-3
(cloud-free), 10 g m-3 (thin cloud), and 50 g m-3 (thick
cloud), respectively. Panel (a) represents light aerosol
conditions with an AOD of 0.25, and panel (b) represents heavy
aerosol conditions with an AOD of 2.5.
High HONO concentrations in daytime are becoming a significant source of OH
radicals. As a result, the OH production rate (P[HOx]) can be written according to the
following reactions.
R3P2HOx=J2×[HONO]R4PHOx=P1HOx+P2HOx=J1O3/k1×am×2.0×k2H2O+J2×[HONO]
Because the chemical lifetime of OH is less than a second, OH concentrations
can be calculated according to the equilibrium of chemical production and
chemical loss. With both OH chemical production processes, the OH
concentrations can be calculated by the following equation (Seinfeld and
Pandis, 2006):
P1+P2=L1+L2,
where P1 and P2 represent the major chemical production expressed in Reaction (R4), and L1
and L2 are the major chemical loss of OH represented by
R5L1:OH+NO2→HNO3,R6L2:HO2+HO2→H2O2+O2.
Under high NOx conditions, such as in the large cities in eastern China, NOx
concentrations were often higher than 50 ppbv (as shown in Fig. 4). As a
result, the L1 term is larger than L2. The OH concentrations can be
approximately expressed as
[HO]=J1O3/k1×am×2.0×k2[H2O]+J2×[HONO]/k3NO2,
where k3 is the reaction coefficient of OH+NO2→HNO3.
Results and analysisOH production in different HONO conditions
In order to quantify the individual effects of these two OH production terms
(P1 and P2) on the OH concentrations, P1 and P2 are calculated under
different daytime HONO conditions (calculated low HONO and measured high
HONO concentrations). Figure 10 shows that under low HONO conditions,
P1 is significantly higher than P2, and P2 has only a minor contribution to
the OH values. For example, the maximum of P1 occurred at 13:00 CST, with a
value of 65×106 no. cm-3 s-1. In contrast, the
maximum of P2 occurred at 10:00 CST, with a value of 15×106
no. cm-3 s-1. However, under high HONO conditions, P2 plays very
important roles for OH production. The maximum of P2 occurred at 11:00 CST,
with a value of 350×106 no. cm-3 s-1, which is about
500 % higher than the P1 value. It is important to note that this
calculation is based on high aerosol conditions (AOD = 2.5) in
September. This result can explain the high O3 chemical production in
Fig. 4.
OH in different aerosol conditions
We seek to understand the effect of aerosol conditions, especially high
aerosol conditions, on OH concentrations. Figure 11 shows OH
concentrations with and without the HONO production of OH. With including the
HONO production (i.e., including P1 and P2), the calculated OH
concentrations are significantly higher than without including this
production (i.e., only including P1). Both calculated OH concentrations
are rapidly changed with different levels of aerosol conditions. For
example, without HONO production, the maximum OH concentration is about
7.5×105 no. cm-3 under low aerosol conditions
(AOD = 0.25). In contrast, the maximum OH concentration was rapidly reduced to
1.5×105 no. cm-3 under high aerosol conditions
(AOD = 2.5) and further decreased to 1.0×105 no. cm-3
with the AOD value of 3.5. In contrast, with including HONO production, the
OH concentrations significantly increased. Under higher aerosol conditions
(AOD = 2.5), the maximum OH concentration is about 7.5×105
no. cm-3, which is the same value under low aerosol conditions in the
no-HONO case. This result suggests that measured high O3 production
occurring in high aerosol conditions is likely due to the high HONO
concentrations in Shanghai.
Effects of clouds
Cloud cover can have very important impacts on the photolysis of HONO, which
can affect the effect of HONO on OH radicals. The above calculations are
based on cloud-free conditions, with a heavy aerosol concentration in the
Beijing region. As shown in Fig. 5, during the case study period (5 to 6 October 2015) (see Fig. 4), the weather map shows cloud-free conditions
with heavy aerosol conditions.
In order to understand the effects of cloud on the photolysis of HONO, we
include different cloud cover in the TUV model. The calculated results are shown
in Fig. 12. The results show that thin cloud (with cloud cover at 2 km
and cloud water of 10 g m-3) could reduce the photolysis rate of HONO
by about 40 %, but the HONO could still have important effects. However,
with dense cloud conditions (with cloud cover at 2 and 3 km and cloud water
of 50 and 10 g m-3), the photolysis rate of HONO could be reduced by 9–10 times
by the cloud. In this case, adding the photolysis rate of HONO cannot produce
an important effect on OH radicals and the production of O3.
OH in winter
The measurement of O3 also shows that the concentrations in winter were
always low (see Fig. 2), suggesting that the O3 concentrations were not
significantly affected by the appearance of HONO. Figure 13 shows the OH
concentrations in September and December. It shows that under different
aerosol conditions, OH concentrations in December were very low compared
with the values in September. Both the calculated OH concentrations include
the HONO production term. For example, under the condition of AOD = 2.5, the
maximum OH is about 7.5×105 no. cm-3 in September, while
it is rapidly reduced to 1.5×105 no. cm-3 in December.
Under the condition of AOD = 3.5, the maximum OH is still maintained at a
relatively high level (4.5×105 no. cm-3) in September.
However, the maximum OH values are extremely low in December, with maximum
value of 0.5×105 no. cm-3. Because both types of
OH chemical production (P1 and P2) are strongly dependent upon solar
radiation (see Reaction R4), the seasonal variation of solar radiation
plays important roles for controlling the OH production in winter (see Fig. 13). Because the solar radiation is at a very low level in winter, adding
the photolysis of HONO has a smaller effect in winter than in other seasons,
and OH remains at low values by including the HONO production term.
The calculated OH concentrations in September (blue bars) and
December (dark red bars) under different aerosol levels.
Summary
Currently, China is undergoing rapid economic development, resulting in a
high demand for energy and greater use of fossil fuels. As a result, high
emissions of pollutants produce heavy aerosol pollution (PM2.5) in
eastern China, such as in the megacity of Beijing. Long-term
measurements show that in addition to heavy aerosol pollution,
O3 is becoming another major pollutant in the Beijing region.
The measured results show that there was very strong seasonal variation in
the concentrations of both PM2.5 and O3 in the region. During
winter, the seasonal variability of O3 concentrations was
anticorrelated with PM2.5 concentrations. However, from late
spring to early fall, the correlation between PM2.5 and O3
concentrations was positive compared to negative in winter. This result
suggests that during heavy aerosol conditions (solar radiation was
depressed), the O3 chemical production was still high, appearing as a
co-occurrence of high PM2.5 and O3 in some cases from late spring
to early fall. This co-occurrence of high PM2.5 and O3 is the
focus of this study. The results are highlighted as follows.
There are high daytime HONO concentrations in major Chinese megacities,
such as Beijing and Shanghai. It is also interesting to note that
high HONO concentrations occurred during high aerosol concentration
periods. Under high daytime HONO concentrations, HONO can be
photodissociated to OH radicals and become an important part of the process to
produce OH.
With including the OH production of measured HONO concentrations, the
calculated OH concentrations are significantly higher than without including
this production. For example, without HONO production, the maximum OH
concentration is about 7.5×105 no. cm-3 under low
aerosol conditions (AOD = 0.25) and is rapidly reduced to 1.5×105 no. cm-3 under high aerosol conditions (AOD = 2.5) in
September. In contrast, by including HONO production, the OH concentrations
significantly increased. For example, under higher aerosol conditions
(AOD = 2.5), the maximum OH concentration is about 7.5×105
no. cm-3, which is similar to the value under low aerosol conditions in
the no-HONO case. This result suggests that even under high aerosol
conditions, the chemical oxidizing process for O3 production can be
active. This result is likely to explain the co-occurrence of high
PM2.5 and high O3 from late spring to early in eastern China.
The measurement of O3 also shows that the concentrations in winter were
always low, suggesting that the O3 concentrations were not
significantly affected by the appearance of HONO. The calculated result
shows that the seasonal variation of solar radiation plays important roles
for controlling the OH production in winter. Because solar radiation is
at a very low level in winter, adding the photolysis of HONO has a smaller
effect in winter than in other seasons, and OH remains at low values by
including the HONO production term.
In recent years, PM2.5 pollution has been reduced due to the large
control efforts by the Chinese government, but O3 pollution has become
another severe pollution problem in eastern China. This study is important
because it provides some significant scientific insight to better
understand O3 pollution in eastern China.
Data availability
The data used in this paper can be provided upon request
from Xuexi Tie (tiexx@ieecas.cn).
Author contributions
XT came up with the original idea of investigating the
scientific issue. XT and JX designed the analysis method. XL, GL, JC, and SZ
provided the observational data and helped in discussion. XT prepared the
paper with contributions from all coauthors.
Competing interests
The authors declare that they have no conflict of interest.
Acknowledgements
This work was supported by the National Natural Science Foundation of China
(NSFC) under grant nos. 41430424 and 41730108. The authors are grateful for
support from the Center for Excellence in Urban Atmospheric Environment,
Institute of Urban Environment, Chinese Academy of Sciences.
Financial support
This research has been supported by the National Natural Science Foundation of China (grant nos. 41430424 and 41730108).
Review statement
This paper was edited by Jianping Huang and reviewed by two anonymous referees.
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