Severe Surface Ozone Pollution in China: A Global Perspective

Lu, Xiao; Hong, Jongsuk; Zhang, Lin; Cooper, O. R.; Schultz, Martin; Xu, Xiangde; Wang, Tao; Gao, Meng; Zhao, Yuanhong; Zhang, Yuanhang

doi:10.1021/acs.estlett.8b00366

Cited by 716 publications

(441 citation statements)

References 54 publications

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“…As a result, O 3 has became the primary air pollutant affecting the ambient air quality instead of PM 2.5 in Shanghai. A similar issue has also occurred in other cities in the eastern China (Lu et al, 2018). For example, the mean PM 2.5 mass concentration over the 74 major cites decreased by 40 % from 2013 to 2017, whereas the maximum daily 8 h average O 3 concentration in summer exceeds the Chinese National Ambient Air Quality Stand (GB3095-2012) over most of eastern China (Li et al, 2019).…”

Section: Introductionmentioning

confidence: 59%

Measurement and model analyses of the ozone variation during 2006 to 2015 and its response to emission change in megacity Shanghai, China

Tie

Gao

et al. 2019

Atmos. Chem. Phys.

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The fine particles (PM 2.5 ) in China have decreased significantly in recent years as a result of the implementation of Chinese Clean Air Action Plan since 2013, while the O 3 pollution is getting worse, especially in megacities such as Beijing and Shanghai. Better understanding of the elevated O 3 pollution in Chinese megacities and its response to emission change is important for developing an effective emission control strategy in the future. In this study, we analyze the significant increasing trend of daily maximum O 3 concentration from 2006 to 2015 in the megacity Shanghai with the variability of 0.8-1.3 ppbv yr −1 . It could likely be attributed to the notable reduction in NO x concentrations with the decreasing rate of 1.86-2.15 ppbv yr −1 accompanied by the small change in VOCs during the same period by excluding the weak trends of meteorological impacts on local dispersion (wind speed), regional transport (wind direction), and O 3 photolysis (solar radiation). It is further illustrated by using a state-of-the-art regional chemical and dynamical model (WRF-Chem) to explore the O 3 variation response to the reduction in NO x emissions in Shanghai. The control experiment conducted for September of 2009 shows excellent performance for O 3 and NO x simulations, including both the spatial distribution pattern and the day-by-day variation through comparison with six in situ measurements from the MIRAGE-Shanghai field campaign. Sensitivity experiments with 30 % reduction in NO x emissions from 2009 to 2015 in Shanghai estimated by Shanghai Environmental Monitoring Center shows that the calculated O 3 concentrations exhibit obvious enhancement by 4-7 ppbv in urban zones with increasing variability of 0.96-1.06 ppbv yr −1 , which is consistent with the observed O 3 trend as a result of the strong VOC-limited condition for O 3 production. The large reduction in NO x combined with less change in VOCs in the past 10 years promotes the O 3 production in Shanghai to move towards an NO x -limited regime. Further analysis of the WRF-Chem experiments and O 3 isopleth diagram suggests that the O 3 production downtown is still under a VOC-limited regime after 2015 despite the remarkable NO x reduction, while it moves to the transition regime between NO x -limited and VOC-limited in sub-urban zones. Supposing the insignificant VOC variation persists, the O 3 concentration downtown would keep increasing until 2020 with the further 20 % reduction in NO x emission after 2015 estimated by Shanghai Clean Air Action Plan. The O 3 production in Shanghai will switch from a VOC-limited to an NO x -limited regime after 2020 except for downtown area, which is likely close to the transition regime. As a result the O 3 concentration will decrease by 2-3 ppbv in sub-urban zones and by more than 4 ppbv in rural areas as a response to a 20 % reduction in NO x emission after 2020, whereas it is not sensitive to both NO x and VOC changes downtown. This result reveals that Published by Copernicus Publications on behalf of the European Geosci...

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Section: Introductionmentioning

confidence: 59%

Measurement and model analyses of the ozone variation during 2006 to 2015 and its response to emission change in megacity Shanghai, China

Tie

Gao

et al. 2019

Atmos. Chem. Phys.

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“…Furthermore, positive trends over East Asia for 2000-2014 are present for a wide range of surface ozone metrics (Chang et al, 2017). Surface observations show ozone further increased over China from 2013 to 2014 to 2016-2017 (Lu et al, 2018).…”

Section: Introductionmentioning

confidence: 92%

Global changes in the diurnal cycle of surface ozone

Strode

Ziemke

Oman

et al. 2019

Atmospheric Environment

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A B S T R A C TChanging emissions of NO x and other ozone precursors drive trends in both production and loss of surface ozone, leading to surface ozone trends that differ according to the time of day. Consequently, the magnitude of the diurnal cycle in surface ozone is changing in several regions of the world. Changes in the diurnal cycle of ozone have implications for the metrics used to assess the impact of ozone on human health and vegetation, since different metrics are sensitive to different portions of the diurnal cycle. We use a high resolution model simulation to examine global changes in the magnitude of the diurnal cycle of O 3 between 1980 and 2015. The simulation reproduces the negative trends in the tropospheric NO 2 column over the eastern United States and Europe, and the positive trends over East Asia, seen by the Ozone Monitoring Instrument (OMI). It also gives a reasonable reproduction of the change in the diurnal cycle of surface ozone seen at rural sites in the eastern United States between the 1990s and 2000s. The simulation shows that the magnitude of the surface O 3 diurnal cycle is increasing in regions with positive changes in NO x emissions, such as South and East Asia, and decreasing in regions with reductions in NO x emissions. It also shows changes in the diurnal cycle of the tropospheric ozone column, although these have fewer regions with statistically significant trends. These changes suggest that daily mean ozone is responding less than the mid-day ozone measured by the Total Ozone Mapping Spectrometer (TOMS) and OMI.

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“…This nationwide network was initiated in January 2013, and this dataset was used to evaluate model performance. This dataset has been extensively employed in previous studies to understand the spatial and temporal variations in air pollution in China (Hu et al, 2016;Lu et al, 2018a) and to reduce uncertainties in estimates of health and climate effects (Gao et al, 2017b). Measurements of air pollutants from the MAPAN (Modeling Air Pollution and Networking) network set up by the Indian Institute of Tropical Meteorology (IITM) under project SAFAR (System of Air Quality and weather Forecasting And Research; Beig et al, 2015) were used in the present study to evaluate the model performance over India.…”

Section: Measurementsmentioning

confidence: 99%

“…China and India are influenced largely by monsoonal climates (Wang et al, 2001), and the seasonality of O 3 in different regions is affected by wind pattern reversals related to the winter and summer monsoon systems (Lu et al, 2018b). Various monsoon indices have been proposed to describe the major features of the Asian monsoon, based on pressure, temperature, and wind fields, etc.…”

Section: Seasonality Of Surface O 3 In Different Regionsmentioning

confidence: 99%

“…Great efforts have been devoted to improving understanding of exceptionally high concentrations (Wang et al, 2006) and the increasing trend in O 3 for both China and India (Beig et al, 2007;Cheng et al, 2016;Ghude et al, 2008;Lu et al, 2018a;Ma et al, 2016;Saraf and Beig, 2004;Xu et al, 2008). Strong but distinctive seasonal variations in O 3 observed in India and China have been linked to higher emissions of precursor gases (Lal et al, 2000) and summer monsoons (Kumar et al, 2010;Lu et al, 2018b;Wang et al, 2017). The contributions of individual economic sectors and source regions were reported based on sensitivity simulations and source apportionment techniques (Gao et al, 2016a;Li et al, , 2016Li et al, , 2012Lu et al, 2019;Wang et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

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Ozone pollution over China and India: seasonality and sources

et al. 2020

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A regional fully coupled meteorology-chemistry model, Weather Research and Forecasting model with Chemistry (WRF-Chem), was employed to study the seasonality of ozone (O 3 ) pollution and its sources in both China and India. Observations and model results suggest that O 3 in the North China Plain (NCP), Yangtze River Delta (YRD), Pearl River Delta (PRD), and India exhibit distinctive seasonal features, which are linked to the influence of summer monsoons. Through a factor separation approach, we examined the sensitivity of O 3 to individual anthropogenic, biogenic, and biomass burning emissions. We found that summer O 3 formation in China is more sensitive to industrial and biogenic sources than to other source sectors, while the transportation and biogenic sources are more important in all seasons for India. Tagged simulations suggest that local sources play an important role in the formation of the summer O 3 peak in the NCP, but sources from Northwest China should not be neglected to control summer O 3 in the NCP. For the YRD region, prevailing winds and cleaner air from the ocean in summer lead to reduced transport from polluted regions, and the major source region in addition to local sources is Southeast China. For the PRD region, the upwind region is replaced by contributions from polluted PRD as autumn approaches, leading to an autumn peak. The major upwind regions in autumn for the PRD are YRD (11 %) and Southeast China (10 %). For India, sources in North India are more important than sources in the south. These analyses emphasize the relative importance of source sectors and regions as they change with seasons, providing important implications for O 3 control strategies.

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Severe Surface Ozone Pollution in China: A Global Perspective

Cited by 716 publications

References 54 publications

Measurement and model analyses of the ozone variation during 2006 to 2015 and its response to emission change in megacity Shanghai, China

Measurement and model analyses of the ozone variation during 2006 to 2015 and its response to emission change in megacity Shanghai, China

Global changes in the diurnal cycle of surface ozone

Ozone pollution over China and India: seasonality and sources

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