et al. 2007). Pearl River Delta (PRD) region of Hong Kong and Guangzhou as well
as Sichuan Basin also exhibited high NO x emissions. Regional distribution of NO x
emissions shown in Fig. 7.5 corresponds very well to the tropospheric NO 2 columns
derived from SCIAMACHY measurements in 2004 (Fig. 7.5b): columns with high
NO 2 concentration were spread across East China and PRD regions in a similar way
as spatial distribution of NO x shown in Fig. 7.5a.
Between 2007 and 2015, provinces with the highest NO x emission in China were
Anhui, Shandong, Henan, Hebei, Jiangsu, Guangdong, Zhejiang, Shanxi, Sichuan,
and Hubei. Combined, emissions from these provinces accounted for 65% of all NO x
emissions in China (van der et al. 2017).
7.4 Spatial-Temporal Pattern of Ground-Level O 3 in China
Fast industrial and urban developments in China led to higher amounts of O 3
precursors (mainly NO x and VOCs) participating and assisting O 3 formation,
which is the reason for high-increasing rate in ground-level O 3 concentrations in
China (Wang and Mauzerall 2004; Feng et al. 2015a).
Ground-level O 3 concentration in China as well as their variations (both spatial
and temporal) was thoroughly analyzed. Li et al. (2017a) collected data on groundlevel O 3 levels at 187 cities from January 2015 to November 2016. Publication and
official release of this data revealed significant spatial variation of O 3 in China.
Averaged O 3 concentrations ranged from 50.6 ppb (in Nanchong) to 64.1 ppb
(in Yixing, which is an industrial city in the Yangtze River Delta). High O 3 levels
were also detected in major Chinese metropolitan areas located in Jing-Jin-Ji and in
deltas of the Yangtze and Pearl Rivers (see Fig. 7.6). Rapid growth and development
of different industries, including transportation and urban branches, in these cities as
well as around them is the major driving force responsible for the O 3 pollution.
Average O 3 concentration over China increased from 46.1 Æ 8.8 ppb in 2014 to
51.9 Æ 7.8 ppb in 2016 (see Fig. 7.6). Significant O 3 level increase was observed in
the Yangtze River Delta, North China Plain, and Inner Mongolian and even Southeastern Tibetan Plateau. However, levels of NO 2 demonstrated a slight decreasing
trend (Li et al. 2017a). We already mentioned above that O 3 increase in different
regions is caused by different factors. Three major factors can be described as
follows. (1) Industrialized areas demonstrate increased ground-level O 3 concentration because of high VOC emissions (Yuan et al. 2013), which, in turn, leads to more
rapid formation of O 3 . (2) In North China Plain, lowered NO x emission inhibits
titration reaction between NO and O 3 , which also results in high O 3 concentrations
(Xu et al. 2016b). (3) High O 3 levels in Tibet Plateau can be explained by strong
stratosphere-troposphere exchange processes because of the narrow troposphere
layer in Tibetan Plateau (Skerlak et al. 2014).
Several studies predicted future changes in ground-level O 3 concentrations in
China. Zhu and Liao (2016) used high-resolution nested grid version of the GEOSChem model to simulate changes in ground-level O 3 concentrations for the
7 Contribution of Atmospheric Reactive Nitrogen to Ozone Pollution in China
143
as Sichuan Basin also exhibited high NO x emissions. Regional distribution of NO x
emissions shown in Fig. 7.5 corresponds very well to the tropospheric NO 2 columns
derived from SCIAMACHY measurements in 2004 (Fig. 7.5b): columns with high
NO 2 concentration were spread across East China and PRD regions in a similar way
as spatial distribution of NO x shown in Fig. 7.5a.
Between 2007 and 2015, provinces with the highest NO x emission in China were
Anhui, Shandong, Henan, Hebei, Jiangsu, Guangdong, Zhejiang, Shanxi, Sichuan,
and Hubei. Combined, emissions from these provinces accounted for 65% of all NO x
emissions in China (van der et al. 2017).
7.4 Spatial-Temporal Pattern of Ground-Level O 3 in China
Fast industrial and urban developments in China led to higher amounts of O 3
precursors (mainly NO x and VOCs) participating and assisting O 3 formation,
which is the reason for high-increasing rate in ground-level O 3 concentrations in
China (Wang and Mauzerall 2004; Feng et al. 2015a).
Ground-level O 3 concentration in China as well as their variations (both spatial
and temporal) was thoroughly analyzed. Li et al. (2017a) collected data on groundlevel O 3 levels at 187 cities from January 2015 to November 2016. Publication and
official release of this data revealed significant spatial variation of O 3 in China.
Averaged O 3 concentrations ranged from 50.6 ppb (in Nanchong) to 64.1 ppb
(in Yixing, which is an industrial city in the Yangtze River Delta). High O 3 levels
were also detected in major Chinese metropolitan areas located in Jing-Jin-Ji and in
deltas of the Yangtze and Pearl Rivers (see Fig. 7.6). Rapid growth and development
of different industries, including transportation and urban branches, in these cities as
well as around them is the major driving force responsible for the O 3 pollution.
Average O 3 concentration over China increased from 46.1 Æ 8.8 ppb in 2014 to
51.9 Æ 7.8 ppb in 2016 (see Fig. 7.6). Significant O 3 level increase was observed in
the Yangtze River Delta, North China Plain, and Inner Mongolian and even Southeastern Tibetan Plateau. However, levels of NO 2 demonstrated a slight decreasing
trend (Li et al. 2017a). We already mentioned above that O 3 increase in different
regions is caused by different factors. Three major factors can be described as
follows. (1) Industrialized areas demonstrate increased ground-level O 3 concentration because of high VOC emissions (Yuan et al. 2013), which, in turn, leads to more
rapid formation of O 3 . (2) In North China Plain, lowered NO x emission inhibits
titration reaction between NO and O 3 , which also results in high O 3 concentrations
(Xu et al. 2016b). (3) High O 3 levels in Tibet Plateau can be explained by strong
stratosphere-troposphere exchange processes because of the narrow troposphere
layer in Tibetan Plateau (Skerlak et al. 2014).
Several studies predicted future changes in ground-level O 3 concentrations in
China. Zhu and Liao (2016) used high-resolution nested grid version of the GEOSChem model to simulate changes in ground-level O 3 concentrations for the
7 Contribution of Atmospheric Reactive Nitrogen to Ozone Pollution in China
143