Introduction
Ozone (O3) in the troposphere is a trace gas of great importance for
climate and air quality. It is the principal precursor of the hydroxyl
radical (OH) which plays a central role in atmospheric chemistry (Seinfeld
and Pandis, 2006), and the third most important greenhouse gas contributing
to the warming of the Earth (IPCC, 2013). At ground level, high levels of
O3 have adverse effects on human health and ecosystem productivity
(National Research Council, 1991; Monks et al., 2015). In the troposphere,
the ambient O3 burden is the product of the flux from the stratosphere
(e.g., Stohl et al., 2003; Lin et al., 2015a), dry deposition, and net
photochemical production involving the reactions of nitrogen oxides
(NOx) with carbon monoxide (CO) and volatile organic compounds (VOCs) in
the presence of sunlight (Crutzen, 1973; Ma et al., 2002). Increases in
anthropogenic emissions of ozone precursors have contributed to changes in
the tropospheric O3 abundances, both globally and regionally (The Royal
Society, 2008; Cooper et al., 2014; Monks et al., 2015; Lin et al., 2015b).
Decadal shifts in climate and circulation regimes can also contribute to
changes in tropospheric O3, as found in the 40-year record at Mauna Loa
Observatory in Hawaii (Lin et al., 2014). Conversely, the changes in
tropospheric O3 may also pose significant feedbacks to the environment
and climate (e.g., Shindell et al., 2012; Stevenson et al., 2013). Therefore,
the long-term changes (or trends) of tropospheric O3 has long been a
topic of great interest in the atmospheric sciences.
Since the 1970s, long-term measurements of surface O3 (and O3
precursors) have been increasingly carried out worldwide, mostly in North
America and Europe (e.g., Logan et al., 2012; Oltmans et al., 2013; Cooper et
al., 2014). The existing knowledge of tropospheric O3 trends has been
recently reviewed (UNEP and WMO, 2011; Cooper et al., 2014; Monks et al.,
2015). Overall, upward trends have been recorded around the world since the
1970s, but trends over the past two
decades have varied regionally. In Europe, the surface O3 in rural or
remote areas, usually regarded as the regional baseline O3, rose until
the year 2000 but has since leveled off or decreased (Logan et al., 2012;
Oltmans et al., 2013; Parrish et al., 2012). In the eastern US, summertime
O3 at most rural and urban stations has decreased over 1990–2010
(Lefohn et al., 2010; Cooper et al., 2012). In the western US, extreme ozone
events have decreased in urban areas, particularly in southern California
(Warneke et al., 2012), but springtime O3 at remote mountain sites has
shown large interannual variability due to stratospheric influence (Lin et
al., 2015a), with little overall trends or small increases (Cooper et al.,
2012; Fine et al., 2015). Analysis of available observations and
chemistry-climate model hindcast indicates that springtime O3 in the
free troposphere over western North America has increased significantly by
0.4 ppbv yr-1 over 1995–2014 (Lin et al., 2015b).
In comparison with North America and Europe, investigations of long-term
O3 trends are scarce in China, where rapid urbanization and
industrialization has occurred over the past 3 decades. Significant
increasing trends of surface O3 have been derived from a handful of
long-term monitoring stations over China, including Beijing (Tang et al.,
2009; Zhang et al., 2014), Hong Kong (Xue et al., 2014), Taiwan (Lin et al.,
2010) and Mount Waligian (Xu et al., 2016). Based on the MOZAIC commercial
aircraft measurements, Ding et al. (2008) derived an O3 increase of
∼ 2 % per year from 1995 to 2005 for the lower troposphere
above Beijing by analyzing the difference between observations from
1995 to 2000 and 2000 to 2005. Wang et al. (2009) reported the first long-term
continuous observations of Chinese surface O3 at a regional background
site in southern China (Hok Tsui), and indicated an average increase of 0.58 ppbv yr-1 during 1994–2007. Xu et al. (2016) recently reported another
continuous O3 record (1994–2013) at Mt. Waliguan, a global atmospheric
watch station in western China, and found significant positive trends with
0.15–0.27 ppbv yr-1 for daytime O3 and 0.13–0.29 ppbv yr-1
for nighttime O3. Despite the valuable information obtained from the
abovementioned efforts, additional studies are required to improve our
understanding of tropospheric O3 trends across the rapidly developing
China. In particular, long-term observations covering more than 10 years
remain very limited over the highly polluted regions of central eastern
China.
Geographical map showing the North China Plain and the location of
Mt. Tai. The left map is color-coded by the HCHO column density in the summer
period (JJA; 2003–2014) retrieved from SCIAMACHY and GOME-2(B).
The observations at Mt. Tai analyzed in the present study.
Year
Month
Observed species
Data source
2003
July–November
O3, CO
Gao et al. (2005) and our study
2004
June–August
O3
Kanaya et al. (2013)a
2005
June–August
O3
Kanaya et al. (2013)a
2006
June–December
O3, NO2∗, NO
Our study
2007
March–December
O3, NO, NO2∗, CO
Our study b
2008
January–December
O3, NO, NO2∗, CO
Our study
2009
January–June
O3, NO, NO2∗, CO
Our study
2014
June–August
O3, NOx∗, CO
Our study c
2015
June–August
O3, NO, NO2∗, CO
Our study c
a Monthly average data were taken from Kanaya et
al. (2013). b Valid NO and NO2∗ data were only
available in March–April and July–December, and CO was available in
March–April in 2007. c Note that the intensive measurement
periods were 6 June–3 July and 24 July–26 August in 2014 and
14 June–8 August in 2015.
In recent years, China has implemented a series of stringent air quality
control measures. Following the successful reductions in sulfur dioxide
(SO2) emissions since 2006 (Lu et al., 2010), China has recently
launched a national programme to reduce NOx emissions during its
“Twelfth Five-Year Plan” (2011–2015) (China State Council, 2011).
However, to our knowledge, fewer controls have been placed on VOC emissions
in China. Rather, anthropogenic VOC emissions have continued to increase (Bo
et al., 2008; Wang et al., 2014). Therefore, it is of great interest and
critical importance to evaluate the effect of the current control policy
(i.e., controlling NOx with little action for VOCs) on regional O3
and other secondary air pollution problems in China.
Mt. Tai (36.25∘ N, 117.10∘ E; 1534 m altitude) is the
highest mountain in the center of the North China Plain (NCP; see Fig. 1) –
a fast developing region facing severe air pollution. During daytime, the
summit is well within the planetary boundary layer (PBL), and the site is
therefore regionally representative of the region (Kanaya et al., 2013).
Since 2003, several field measurement campaigns have been conducted at this
site, with surface O3 of major interest. In this paper, we analyze all
available O3 and its precursor observations at Mt. Tai to understand the
summertime O3 characteristics, including trends. To place the short
observational record into a long-term context, we analyze multi-decadal
hindcast simulations (1980–2014) conducted with the GFDL-AM3
chemistry-climate model (Lin et al., 2014, 2015a, b). In the following
sections, we first present the seasonal and diurnal ozone variations followed
by the climatological air mass transport pattern in summer. We then derive
the O3 trend (or systematic change) during 2003–2015 using linear
regression. We finally elucidate the key factors affecting the O3 trends
by examining satellite and in situ observed trace gas data. Our analysis
demonstrates a significant increase of summertime surface O3 at this
important regional site in northern China, and indicates the urgent need of
VOC control in China to reduce regional O3 pollution.
Observational data set
The observations analyzed in the present study are summarized in Table 1. It
comprises several sets of field observations from different periods. The
earliest O3 measurements at Mt. Tai were made from July to November 2003
(Gao et al., 2005), and the longest observations lasted for 3 years from
June 2006 to June 2009 (despite a data gap in January–February 2007 owing
to instrument maintenance). In recent years, we conducted intensive
measurements at Mt. Tai during June–August of 2014 and 2015. In addition,
another set of 3-year measurements was carried out from March 2004 to May 2007, as an international joint effort between Japanese and Chinese
scientists (Kanaya et al., 2013); monthly average O3 data are taken
from this work. As most of the measurements are available for the period of
June–August each year, we focus on the summertime O3 in this study.
Two study sites have been used for field observations at Mt. Tai. One was
the Mt. Tai Meteorological Observatory (Site 1) at the summit with an
altitude of 1534 m a.s.l., and the other was in a hotel (Site 2) that is
∼ 1 km to the northwest of Site 1 and slightly lower (1465 m a.s.l.; see Fig. S1 in the Supplement for the site locations). Such elevations position these sites
either within the PBL in the afternoon in summer, or in the free troposphere
during the night. Although Mt. Tai is a famous tourism spot, both sites are
located in the less frequently visited zones. Hence the impact of local
anthropogenic emission should be small, and the data collected are believed
to be regionally representative. Details of these sites have been described
elsewhere (Site 1: Gao et al., 2005; Kanaya et al., 2013; Site 2: Guo et
al., 2012; Shen et al., 2012). For our data set, most of the measurements
were taken at Site 1, and only the intensive campaign in 2014 took place at
Site 2.
All measurements were implemented using standard techniques, which were
detailed in the previous publications (e.g., Gao et al., 2005; Xue et al.,
2011). Briefly, O3 was measured using a commercial ultraviolet
photometric instrument (Thermo Environment Instruments (TEI), Model 49C) with a detection limit of 2 ppbv and a precision
of 2 ppbv. CO was monitored with a gas filter correlation, non-dispersive
infrared analyzer (Teledyne Advanced Pollution Instrumentation, Model 300E), with automatic zeroing every 2 hours. This technique
has a detection limit of 30 ppbv and a precision of 1 % for a level of 500
ppbv. NO and NO2∗ were measured by a chemiluminescence analyzer
equipped with an internal MoO catalytic converter (TEI, Model 42C), with a detection limit
of 0.4 ppbv and precision of 0.4 ppbv. Inter-comparison with a highly
selective photolytic NO2 detection approach indicated that the
NO2∗ measured with MoO conversion significantly overestimated NO2
(i.e., up to 130 % in afternoon hours), and NO2∗ actually represented
a major fraction (60–80 %) of NOy at Mt. Tai (Xu et al., 2013).
During the measurements, the O3 analyzer was calibrated routinely
(i.e., quarterly for the 3-year observations in 2006–2009, and before and
after the other campaigns) by an ozone primary standard (TEI, Model 49PS). For CO and
NOx∗, zero and span calibrations were performed weekly during
2006–2009 and every 3 days during the intensive campaigns.
Meteorological data including temperature, relative humidity (RH), and wind
vectors were obtained from the Mt. Tai Meteorological Observatory, where
Site 1 is located.
It is noteworthy that some portion of this long-term data set has been
reported previously. Gao et al. (2005) analyzed the measurements of O3
and CO from July to November 2003 and examined their diurnal variations and
relations to backward trajectories. Kanaya et al. (2013) reported the
observations in 2004–2007 and examined the processes influencing the
seasonal variations and regional pollution episode. The major objective of
the present study is to compile all of the available O3-related
observations at Mt. Tai and to establish the trend (or systematic change),
if any, of ambient O3 levels in the past decade at this unique site,
regionally representative of the North China Plain.
Results and discussion
Seasonal and diurnal variations from more recent data
Figure 2 depicts the seasonal variation of surface O3 at Mt. Tai derived
from the more recent year-round observations from 2006 to 2009. Overall,
O3 shows higher levels in the warm season, i.e. April–October, compared
to the cold season, i.e. November–March, with two peaks in June and October.
The elevated O3 levels in April and May should be affected by the
stratosphere-troposphere exchange process which usually occurs at its maximum
in the spring season (Yamaji et al., 2006). In addition to the high
temperatures and intense solar radiation (especially in June), biomass
burning is believed to be another factor shaping the O3 maximums in June
and October, both of which are major harvest seasons of wheat and corn in
northern China. The significant impacts of biomass burning on air quality
over the North China Plain during June have been evaluated by a number of
studies (Lin et al., 2009; Yamaji et al., 2010; Suthawaree et al., 2010). It
is also noticeable that the O3 concentrations in July and August at
Mt. Tai are substantially lower than those in June. This is attributed in
part to the more humid weather and greater precipitation in July and August
in this region (see Table 2 for the RH condition). Inspection of
meteorological conditions day by day also indicates a frequency of cloudy
days (i.e., with RH ≥ 95 %) of ∼ 25 % in June and of
∼ 51 % during July–August. In the following analyses, therefore,
we assess the ozone characteristics separately for June and July–August.
Seasonal variation of surface O3 mixing ratios at Mt. Tai
derived from the continuous observations from 2006 to 2009. Red dots indicate
the monthly average O3 concentrations. Shown in the upper panel is the
frequency of the MDA8 O3 exceeding the Chinese national ambient air
quality standard, i.e. 75 ppbv (Class II).
Summary of meteorological conditions recorded at Mt. Tai in June and
July–August over 2003–2015∗.
Year
June
July–August
Temperature
RH
Prevailing
Temperature
RH
Prevailing
(∘C)
(%)
WD
(∘C)
(%)
WD
2003
15.4 ± 3.1
70.9 ± 19.2
SW
17.3 ± 2.9
88.3 ± 16.3
SW
2004
15.4 ± 3.9
74.4 ± 21.2
SW
17.0 ± 2.5
86.8 ± 15.5
SSW
2005
18.1 ± 3.2
65.0 ± 22.0
SSW
17.4 ± 2.9
86.8 ± 16.3
SW
2006
17.2 ± 2.9
67.8 ± 21.4
SSW
18.3 ± 2.0
88.3 ± 16.3
SSW
2007
17.0 ± 2.8
71.4 ± 27.3
E
17.8 ± 2.3
85.2 ± 21.1
E
2008
15.0 ± 3.6
76.9 ± 20.0
S
17.0 ± 2.3
86.3 ± 14.6
S
2009
17.9 ± 3.1
57.8 ± 22.2
SSW
17.4 ± 2.9
78.7 ± 21.8
S
2010
15.9 ± 3.6
80.1 ± 18.7
SW
18.2 ± 2.7
91.0 ± 16.9
SW
2011
16.6 ± 2.7
72.6 ± 21.1
SSW
17.6 ± 2.5
87.6 ± 16.1
S
2012
16.8 ± 3.2
71.0 ± 23.8
SW
18.2 ± 2.4
89.5 ± 17.9
E
2013
16.1 ± 3.1
79.8 ± 19.6
SW
19.3 ± 2.4
88.2 ± 15.6
SW
2014
15.3 ± 2.9
79.9 ± 17.6
SW
16.5 ± 2.3
86.7 ± 14.6
SW
2015
15.8 ± 2.8
70.5 ± 21.0
SW
18.0 ± 2.1
86.1 ± 16.9
SW
∗ Average and standard deviations are provided.
Shown in the upper panel of Fig. 2 is the frequency of the maximum daily
8-hour average O3 mixing ratios (MDA8 O3) exceeding the 75-ppbv
National Ambient Air Quality Standard (Class II). Although located in a
relatively remote mountain-top area, the observed O3 pollution at Mt. Tai was rather serious in the warm season, with frequencies of the
O3-exceedence days of over 45 % throughout April–October. In
particular, the occurrence of O3-exceedence days was as high as 89 %
in June. These results demonstrate the severe O3 pollution situation
across the North China Plain.
Average diurnal variations of surface O3 at Mt. Tai in
(a) June and (b) July-August derived from the continuous
observations from 2006 to 2009. The shaded area indicates the 5th and 95th
percentiles of the data.
Figure 3 illustrates the well-defined diurnal variations of surface O3
with a trough in the early morning and a broad peak lasting from afternoon
to early evening, which is commonly observed at polluted rural sites. As the
summit of Mt. Tai is well above the PBL at nighttime, the O3
concentrations during the latter part of the night (e.g., 02:00–05:00 LT) are
usually considered to reflect the regional baseline O3 (defined
hereafter as regional O3 without impact of local photochemical
formation). Comparing the diurnal profiles in June and July–August clearly
reveals the significantly higher regional baseline O3 in June (with a
mean difference of ∼ 17 ppbv). On the other hand, the daytime
O3 build-up, defined as the increase in O3 concentrations from the
early-morning minimum to the late-afternoon maximum, may reflect the
potential of regional O3 formation. For the Mt. Tai case, the average
daytime O3 build-up was 22 ppbv in June and 15 ppbv in July–August,
indicating the stronger photochemical ozone production in June. Hence, the
more intense photochemistry and higher regional baseline bring about the
more serious O3 pollution in June at Mt. Tai.
Another remarkable feature of surface O3 at Mt. Tai is the relatively
high nighttime levels, with average concentrations of 75–85 ppbv in June
and 60–70 ppbv during July–August. This should be the composite result of
the residual O3 produced in the preceding afternoon in the boundary
layer, less O3 loss from NO titration, and long-range transport of
processed regional plumes. The transport of regional plumes was evidenced by
the coincident evening NO2∗ (including NO2 and some higher
oxidized nitrogen compounds) maximums and relatively low NO levels
(indicative of the aged air mass), as shown in Fig. 4. Inspection of the
time series day by day also reveals the frequent transport of
photochemically aged air masses containing elevated concentrations of
O3 (over 100 ppbv), CO and NO2∗ to the study site during the late
evening (figures not shown). Similarly, the MOZAIC aircraft measurements
have also found ∼ 60 ppbv on average of O3 at around 1500 m a.s.l. over Beijing at 05:00–06:00 LT in summer (i.e., May–July; Ding et
al., 2008), which is comparable to what we observed at Mt. Tai. These
results imply the existence of the O3-laden air in the nocturnal
residual layer over the North China Plain region. Moreover, Ding et al. (2008) also showed in their Fig. 11 that the O3 enhancement extended
from the surface up to about 2 km, further evidence that during the daytime
Mt. Tai should be within the boundary layer and is sampling at a vertical
level where ozone enhancements are expected.
Average diurnal variations of (a) NO2∗ and
(b) NO at Mt. Tai in June and July–August derived from the
continuous observations from 2006 to 2009. The shaded area indicates the
standard error of the mean.
Impact of long-range transport
Long-range transport associated with synoptic weather and large-scale
circulations is an important factor for the variation of O3 in rural
areas (Wang et al., 2009; Ding et al., 2013; Lin et al., 2014; Zhang et al.,
2016). To elucidate the history of air masses sampled at Mt. Tai, we analyzed
the summertime climatological air mass transport pattern during 2003–2015
with the aid of cluster analysis of back trajectories. The NCEP reanalysis
data and GDAS archive data (http://ready.arl.noaa.gov/archives.php)
were used to compute trajectories during 2003–2004 and 2005–2015. The
detailed methodology has been documented by Wang et al. (2009) and Xue et
al. (2011). Briefly, three-dimensional 72-hour back trajectories were
computed four times a day (i.e., 02:00, 08:00, 14:00 and 20:00 LT) for
June–August with the Hybrid Single-Particle Lagrangian Integrated Trajectory
model (HYSPLIT, v4.9; Draxler et al., 2009), with an endpoint of 300 m above
ground level exactly over Mt. Tai. All the trajectories were then categorized
into a small number of major groups with the HYSPLIT built-in cluster
analysis approach. Total spatial variance (TSV) and the variance between each
trajectory component were calculated to determine the optimum number of
clusters (Draxler et al., 2009).
A total of five air mass types were extracted for the summer period, with
four identified for June and July–August respectively. These air mass types
are named according to the regions they traversed, and are described as
follows: “Marine and East China” (M&EC) – air masses from the
southeast passing over the ocean and polluted central eastern China;
“Northeast China” (NEC) – air masses from the north passing over
Northeast China; “Central China” (CC) – air masses from the south moving
slowly over central China; “Southeast China” (SEC) – air masses from the
south moving fast from southeast China; “Mongolia and North China”
(M&NC) – air masses from the northwest passing over Mongolia and central
northern China.
The above identified major types of air masses are presented in Fig. 5. In
June, M&EC was most frequent (57 %), followed by CC (26 %), NEC
(9 %) and M&NC (8 %; only identified in June). During the
July–August period, the most frequent air mass type was still M&EC
(36 %), then CC (29 %) and NEC (29 %), with a minor fraction of SEC
(6 %; only identified in July–August). Overall, the transport patterns in
June and July–August are quite similar, and it is evident that southerly
and easterly air flows (e.g., M&EC and CC) dominated the air mass
transport to Mt. Tai in summer. Such patterns are believed to be driven by
the summer Asian monsoon (Ding et al., 2008).
Climatological air mass transport pattern at Mt. Tai in
(a) June and (b) July–August over 2003–2015. The maps are
color-coded by the NO2 column density retrieved from SCIAMACHY
(2003–2011) and GOME-2(B) (2013–2015). The box (dashed line) refers to the
domain for which the satellite retrievals were averaged. Five major air
masses: (1) M&EC: Marine and East China, (2) NEC: Northeast China, (3) CC:
Central China, (4) SEC: Southeast China, (5) M&NC: Mongolia and North
China.
Statistics of O3, NO2∗ and CO in different air mass
categories.a.
June
July–August
Air massb
O3
NO2∗
CO
Air massb
O3
NO2∗
CO
M&EC
92 ± 27
7.2 ± 5.3
500 ± 300
M&EC
64 ± 22
3.6 ± 2.9
370 ± 180
CC
89 ± 24
6.3 ± 5.0
550 ± 300
CC
77 ± 21
3.3 ± 2.5
440 ± 180
NEC
94 ± 25
7.0 ± 4.5
380 ± 180
NEC
73 ± 22
4.5 ± 4.2
380 ± 180
M&NC
78 ± 21
4.0 ± 3.3
280 ± 180
SEC
58 ± 17
4.1 ± 2.4
350 ± 80
a The unit is ppbv; average and standard deviations
are provided. b Refer to Fig. 5 and Sect. 3.2 for the derivation
and description of the air mass types.
The chemical signatures of the different air masses were also inspected and
summarized in Table 3. The air masses of M&EC, CC and NEC, which passed
over several polluted regions of eastern China, contained higher abundances
of O3 (with averages of 89–94 ppbv in June and 64–77 ppbv in
July–August), CO and NO2∗. In comparison, the more aged air masses of
M&NC and SEC showed relatively lower concentrations of O3 (78 ± 21 ppbv for M&NC in June and 58 ± 17 ppbv for SEC in July–August)
and its precursors (except for NO2∗ in the SEC air mass). In view of
the higher frequency and higher O3 levels of the M&EC, CC and NEC
air masses, it could be concluded that the regions with the greatest
influence on O3 at Mt. Tai in summer are primarily located in the
southern and eastern parts of central eastern China.
Observed ozone trend
Figure 6 presents the monthly average hourly O3 and MDA8 O3 mixing
ratios in June and July–August whenever available from 2003 to 2015 at Mt. Tai. The least square linear regression analysis reveals the significant
increase of surface O3 at Mt. Tai since 2003. Monthly mean O3
values based on hourly data increased at rates of 1.7 ± 1.0 ppbv yr-1 (±95 % confidence intervals)
in June and 2.1 ± 0.9 ppbv yr-1 in July–August, and the increases were statistically
significant (p < 0.01). For the monthly means based on MDA8 O3,
the fewer available data points (as we only have monthly average data during
2004–2005 from Kanaya et al., 2013) likely reduced the significance of the
trend in June, with a positive by statistically insignificant increase (rate = 1.4 ± 1.9 ppbv yr-1; p=0.12). However the site had a
significant positive trend in July–August (rate = 2.2 ± 1.2 ppbv yr-1; p < 0.01). Therefore we conclude that summertime surface
O3 levels at Mt. Tai have increased over the period 2003–2015.
Given the fact that Mt. Tai is above the PBL at night when there is no
photochemistry, the ambient O3 levels before dawn (e.g., 02:00–05:00 LT)
are representative of the regional baseline O3. The diurnal variation
in Fig. 3 shows a slight but steady decrease in O3 concentrations
overnight, which should arise from dry deposition. It was assumed that dry
deposition was essentially the same every year and did not affect the
derived trends. Figure 7 shows the monthly averaged late-night O3
mixing ratios in June and July–August available from 2003 to 2015 at Mt. Tai.
Again, positive trends were found. The rate of increase was quantified at
1.9 ± 1.8 ppbv yr-1 (p=0.04, significant) in June and
1.1 ± 1.2 ppbv yr-1 (p=0.06, insignificant) during
July–August. The increase of regional baseline likely explains the observed
O3 rise at Mt. Tai in June and also accounts for the majority of the
increase during July–August. These results indicate the significant
increase of surface O3 in summer on the regional scale across northern
China.
Summary of surface and lower tropospheric ozone trends recorded in
East Asia.
Station
Site type
Period
Rate of change (ppbv yr-1)
Reference
Mt. Tai
rural
2003–2015 (summer)
1.7 ± 1.0 (June)
This study
2.1 ± 0.9 (July–August)
Beijing
rural (MOZAIC)
1995–2005
∼ 1 (annual average)
Ding et al. (2008)
∼ 3 (summer afternoon)
Hong Kong (Hok Tsui)
rural
1994–2007
0.58
Wang et al. (2009)
Hong Kong
urban & suburban
2002–2013 (autumn)
0.54 ± 0.49
Xue et al. (2014)
Lin'an
rural
1991–2006
2.7 % (summer daily maximum)
Xu et al. (2008)
Waliguan
remote
1994–2013 (summer)
0.15 ± 0.19
Xu et al. (2016)
Taiwan (Yangming)
rural
1994–2007
0.54 ± 0.21
Lin et al. (2010)
Mt. Happo, Japan
rural
1991–2011 (summer)
0.64 ± 0.40
Parrish et al. (2012)
Tokyo, Japan
urban & suburban
1990–2010
0.31 ± 0.02
Akimoto et al. (2015)
Nagoya, Japan
urban & suburban
1990–2010
0.22 ± 0.05
Akimoto et al. (2015)
Osaka/Kyoto, Japan
urban & suburban
1990–2010
0.37 ± 0.03
Akimoto et al. (2015)
Fukuoka, Japan
urban & suburban
1990–2010
0.37 ± 0.04
Akimoto et al. (2015)
South Korea
124 urban sites average
1999–2010
0.26
Seo et al. (2014)
South Korea
56 urban sites average
1990–2010
0.48 ± 0.07 (annual average)
Lee et al. (2013)
0.55 ± 0.13 (summer)
Monthly averaged (a) 1-hour and (b) MDA8 O3
mixing ratios at Mt. Tai in June and July–August over 2003–2015. Error bars
indicate the standard deviation of the mean. The
black open circles and squares represent the data
taken from Kanaya et al. (2013). The fitted lines are derived from the least
square linear regression analysis with the slopes (±95 % confidence
intervals) and p values annotated.
Monthly averaged nighttime O3 mixing ratios (inferring the
regional background O3) at Mt. Tai in June and July–August over
2003–2015. Error bars indicate the standard deviation of the mean. The
fitted lines are derived from the least square linear regression analysis
with the slopes (±95 % confidence intervals) and p values
annotated.
Table 4 compares the surface and lower tropospheric ozone trends available in
East Asia in recent decades. Two aspects are particularly noteworthy from
this comparison. First, most studies have deduced significant positive trends
demonstrating the broad increase of tropospheric O3 over East Asia,
especially in China. This pattern is distinct from that found in Europe and
the eastern U.S., where O3 levels have begun to decrease or level off
since the 1990s or 2000s (e.g., Cooper et al., 2014; Lefohn et al., 2010;
Oltmans et al., 2013; Parrish et al., 2012). The O3 increase in East
Asia is expected due to the rapid economic growth and increasing
anthropogenic emissions of O3 precursors in the past 3 decades
(e.g., Ohara et al., 2007). Second, the magnitude of O3 increase is
quite heterogeneous in different regions and the fastest rise was found in
the North China Plain. For example, the rates of O3 increase were in the
range of 0.54–0.58 ppbv yr-1 in Hong Kong (1994–2007, Wang et al.,
2009; 2002–2013, Xue et al., 2014), 0.54 ppbv yr-1 in Taiwan
(1994–2007, Lin et al., 2010), 0.26–0.55 ppbv yr-1 over South Korea
(1990–2010, Lee et al., 2013; 1999–2010, Seo et al., 2014),
0.22–0.37 ppbv yr-1 in major Japanese metropolitan areas (1990–2010;
Akimoto et al., 2015), 0.64 ppbv yr-1 at Mt. Happo, Japan (1991–2011,
summer scenario; Parrish et al., 2014), and 0.15 ppbv yr-1 at
Mt. Waliguan, a GAW station in western China (1994–2013, summer scenario; Xu
et al., 2016). According to the MOZAIC aircraft observations, in comparison,
Ding et al. (2008) have reported the PBL O3 increases of
∼ 1 ppbv yr-1 for the annual average and
∼ 3 ppbv yr-1 for the summer afternoon peaks over the period of
1995–2005. Zhang et al. (2014) analyzed their field measurements at an urban
site in Beijing during 2005–2011 and quantified an increasing rate of
2.6 ppbv yr-1 for the daytime average O3 in summer. Comparable
rates of O3 increase (1.7–2.1 ppbv yr-1) were determined in the
present study from the measurements of longer time coverage and at a more
regionally representative mountain site, affirming the significant rise of
surface O3 levels over the North China Plain region. Furthermore, the
magnitude of O3 increase in this region is also among the highest
records currently reported in the world (Cooper et al., 2012, 2014; Lin et
al., 2014; Parrish et al., 2014).
Comparison with multi-decadal chemistry-climate simulations
We draw on a multi-decadal GFDL-AM3 chemical transport model simulation to
provide context for the trends derived from the short observation record. In
contrast to the free-running models used in Cooper et al. (2014) that
generate their own metrology, the GFDL-AM3 simulations used in the present
study are relaxed to the NCEP/NCAR reanalysis using a pressure-dependent
nudging technique (Lin et al., 2012) and thus allow for an apples-to-apples
comparison with the observational records. The simulations are described in
detail in a few recent publications, which show that AM3 captures
inter-annual variability and long-term trends of baseline O3 measured at
Mauna Loa Observatory (Lin et al., 2014), western U.S. free tropospheric and
surface sites (Lin et al., 2015a, b). Ozone measurements at Mt. Tai provide
an important test for the model to represent O3 trends in a polluted
region where emissions have changed markedly over the past few decades.
Comparison of ozone trends at Mt. Tai. (a) Anomalies in the
June average of MDA8 O3 from 1980 to 2015 as observed (black dots) and
simulated by the GFDL-AM3 model with time-varying (red circles) and constant
anthropogenic emissions (gray lines). (b) Same as panel (a)
but for the July–August average. The model is sampled in the surface level.
The linear trends over 1980–2014 and 1995–2014, including the 95 %
confidence limits and p-values, are shown.
Figure 8 shows comparisons of O3 trends at Mt Tai as observed and
simulated by the GFDL-AM3 model for June and July-August, respectively. The
model has a mean state ozone bias of 10–20 ppbv as in the other global
models (Fiore et al., 2009). For illustrative purposes, both observations
and model results in Fig. 8 are shown as anomalies. With anthropogenic
emissions varying over time (based on Lamarque et al., 2010, with annual
interpolation after 2000 to RCP 8.5), AM3 simulates significant MDA8 O3
increases of 1.04 ± 0.45 ppbv yr-1 over 1995–2014 for June and
1.65 ± 0.41 ppbv yr-1 for July–August. A greater rate of O3
increase is simulated for July–August with warmer temperatures compared to
June, consistent with the trends derived from the shorter observational
records. With constant emissions, AM3 gives no significant long-term ozone
trends over the entire 1980–2014 period despite large inter-annual
variability (see gray lines in Fig. 8). The model indicates that changes
in regional emissions have raised surface ozone over the North China Plain
by ∼ 30 ppbv in June and ∼ 45 ppbv in
July–August over the past 35 years, with an accelerating trend in the most
recent 20 years.
Roles of meteorology and anthropogenic emissions
To further elucidate the factors contributing to the observed surface
O3 change at Mt. Tai, we examined variations in both meteorological
conditions and anthropogenic emissions of O3 precursors during the past
decade. Table 2 shows year-to-year variability in summertime mean
meteorological conditions including average temperature, RH, and prevailing
wind direction recorded at Mt. Tai over the period of 2003–2015. No
systematic change was found with regard to the overall meteorological
conditions although some variability is clearly shown. For instance,
substantially warmer temperatures were recorded in June 2015 and July–August 2013 as a result of large-scale heat waves (Yuan et al., 2016). During these
years, the GFDL-AM3 model with constant emissions simulates high-O3
anomalies (up to ∼ 10 ppbv) relative to the climatological
mean (Fig. 8), indicating that heat waves can enhance summertime O3
pollution in Central Eastern China. Unfortunately, there were no
observations available in 2005 and 2013. Observations show greater O3
levels during July–August of 2014–2015 compared to 2004–2009 (Fig. 8) but
no significant change in temperature were found between the two time periods
(Table 2), indicating the key role of regional emission changes in
contributing to the observed ozone increase at Mt. Tai.
We also explored the air mass transport pattern deduced from cluster
analysis of back trajectories (see Sect. 3.2) year by year over 2003–2015
(Table S1). Despite the large year-to-year variability, again, no systematic change
in the air mass transport pattern was indicated during the target period.
Although the impact of meteorology on tropospheric O3 is very complex
and might not be quantified by such a simple analysis, the significant
increase of surface O3 observed at Mt. Tai should not primarily arise
from the change in meteorological conditions.
We analyzed the satellite retrievals of formaldehyde (HCHO) and NO2 to
track the variations in the abundances of O3 precursors (i.e., NOx
and VOCs) during the study period. Considering that HCHO is a major
oxidation product of a variety of VOC species and due to the availability of
the satellite-retrieved products, HCHO was selected as an indicator of the
VOC abundances. The satellite data were obtained from SCIAMACHY for
2003–2011 and GOME-2(B) from 2013 onwards, with the Level-2 products taken
from the TEMIS archive (Tropospheric Emission Monitoring Internet Service;
http://www.temis.nl/index.php). Considering the geographical
representativeness of Mt. Tai, a larger domain (32–38∘ N, 115–120∘ E; see Fig. 5) was selected to
process the regional mean satellite data. The monthly averaged HCHO and
NO2 column densities in June and July–August from 2003–2015 are
documented in Fig. 9. Significant positive trends are seen for HCHO, with
rates of 2.7± 2.2 % (p=0.02) for June and 2.2 ± 1.4 % (p < 0.01) for July–August, indicative of the strong increase
of VOCs in this region. This result agrees very well with the emission
inventory estimates which showed significant increases of anthropogenic VOC
emissions in China in the past decades (Bo et al., 2008; Wang et al., 2014),
and is consistent with the lack of nationwide VOC controls. All of these
results evidence the increase of atmospheric VOC abundances over the North
China Plain.
Monthly average column density of (a) formaldehyde and
(b) NO2 retrieved from SCIAMACHY (2003–2011; solid markers)
and GOME-2(B) (2013–2015; open markers) for the target domain
(32–38∘ N, 115–120∘ E). For formaldehyde, the fitted
lines are derived from the least square linear regression analysis with the
slopes (±95 % confidence intervals) and p values also shown.
What is more interesting is the two-phase variation of the NO2 column,
showing a significant increase first from 2003 to 2011 (June: 4.8 ± 3.4 %, p=0.01; July–August: 7.7 ± 3.6 %, p < 0.01)
and a decrease afterwards (see Fig. 9b). These satellite observations agree
very well with the bottom-up emission inventory estimates, which clearly
showed a break point occurring in 2011 in the anthropogenic NOx
emissions of China (see Fig. S2). China has just launched a national NOx
control programme during its “Twelfth Five-Year Plan” (i.e., 2011–2015)
(China State Council, 2011). The strict control measures are very efficient
and have resulted in an immediate reduction of NOx emissions, as
affirmed by both emission inventories and satellite retrievals. Furthermore,
the reduced levels of NOx in the most recent 5 years were also
evidenced by our limited in situ NOx∗ measurements at Mt. Tai. As shown
in Fig. 10, the ambient NO2∗ levels in 2014 and 2015 were indeed
substantially lower than those measured in the previous years before 2010.
Monthly averaged NO2∗ concentrations measured at Mt. Tai
in (a) June and (b) July–August during 2006–2015. Error
bars indicate the standard error of the mean. Note that the data point in
June 2014 is for NOx∗ instead of NO2∗.
From the above analyses, the O3 increase between 2003 and 2011 is easy
to understand in light of the consistent increase of both NOx and VOCs.
For the later period, i.e. after 2011, in comparison, opposite trends have
taken place with NOx decreasing but VOCs still increasing. The observed
continuing O3 rise suggests that the reduction of NOx is not
adequate to reduce the ambient O3 levels, with a background of
increasing VOCs. We then evaluated the ozone production efficiency (OPE) for
the air masses sampled at Mt. Tai. OPE is usually derived from the
regression slope of the scatter plots of O3 versus NOz (Trainer et
al., 1993), and is a useful metric to infer how efficient O3 is
produced per oxidation of unit of NOx (e.g., Wang et al., 2010; Xue et
al., 2011). As NOy (and thus NOz) is not routinely measured in the
present study, NO2∗ is used instead of NOz to infer the OPE
values. It should be reasonable considering that our measured NO2∗
significantly overestimated true NO2 and actually contained a large
fraction of NOz, especially in the afternoon period when NOz was
at its maximum with NO2 at the minimum (Xu et al., 2013). The scatter
plots of O3 versus NO2∗ during the afternoon hours (i.e.,
12:00–18:00 LT) available from 2006–2015 at Mt. Tai are presented in Fig. 11. The OPE values in 2014–2015 (i.e., 9.6–15.0) were significantly higher
than those determined during 2006–2009 (i.e., 3.6–7.9). This demonstrates
the greater ozone production efficiency in recent years with increasing
VOCs. These results indicate that although NOx in China has been
reduced since 2011, little action on VOC control has led to increased
emissions of VOCs, which could make O3 formation more efficient per
unit of NOx. As a consequence, ambient O3 levels have been rising
in northern China. We conclude that control of VOCs is urgently needed, in
addition to the ongoing strict NOx control, to mitigate regional
O3 pollution in China.
Scatter plots of O3 versus NO2∗ at Mt. Tai in
(a) June and (b) July–August during 2006–2015. Only the
afternoon data (i.e., 12:00–18:00 local time) were used for this analysis.
Note that the NO2∗ data in June 2014 stand for NOx∗
(NOx∗= NO + NO2∗), of which NO usually presents a
minor fraction. The slopes are determined by the reduced major axis (RMA)
method.