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Spatial and temporal variations of surface background ozone in China analyzed with the grid-stretching capability of GEOS-Chem High Performance.
Ye, Xingpei; Zhang, Lin; Wang, Xiaolin; Lu, Xiao; Jiang, Zhongjing; Lu, Ni; Li, Danyang; Xu, Jiayu.
Afiliação
  • Ye X; Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China.
  • Zhang L; Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China. Electronic address: zhanglg@pku.edu.cn.
  • Wang X; Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China.
  • Lu X; School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai, Guangdong, China.
  • Jiang Z; Environmental and Climate Sciences Department, Brookhaven National Laboratory, Upton, NY 11973-5000, United States of America.
  • Lu N; Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China.
  • Li D; Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China.
  • Xu J; Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China.
Sci Total Environ ; 914: 169909, 2024 Mar 01.
Article em En | MEDLINE | ID: mdl-38185162
ABSTRACT
Surface background ozone, defined as the ozone in the absence of domestic anthropogenic emissions, is important for developing emission reduction strategies. Here we apply the recently developed GEOS-Chem High Performance (GCHP) global atmospheric chemistry model with ∼0.5° stretched resolution over China to understand the sources of Chinese background ozone (CNB) in the metric of daily maximum 8 h average (MDA8) and to identify the drivers of its interannual variability (IAV) from 2015 to 2019. The GCHP ozone simulations over China are evaluated with an ensemble of surface and aircraft measurements. The five-year national-mean CNB ozone is estimated as 37.9 ppbv, with a spatially west-to-southeast downward gradient (55 to 25 ppbv) and a summer peak (42.5 ppbv). High background levels in western China are due to abundant transport from the free troposphere and adjacent foreign regions, while in eastern China, domestic formation from surface natural precursors is also important. We find greater importance of soil nitric oxides (NOx) than biogenic volatile organic compound emissions to CNB ozone in summer (6.4 vs. 3.9 ppbv), as ozone formation becomes increasingly NOx-sensitive when suppressing anthropogenic emissions. The percentage of daily CNB ozone to total surface ozone generally decreases with increasing daily total ozone, indicating an increased contribution of domestic anthropogenic emissions on polluted days. CNB ozone shows the largest IAV in summer, with standard deviations (seasonal means) of ∼5 ppbv over Qinghai-Tibet Plateau (QTP) and >3.5 ppbv in eastern China. CNB values in QTP are strongly correlated with horizontal circulation anomalies in the middle troposphere, while soil NOx emissions largely drive the IAV in the east. El Nino can inhibit CNB ozone formation in Southeast China by increased precipitation and lower temperature locally in spring, but enhance CNB in Southwest China through increased biomass burning emissions in Southeast Asia.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article