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Tropospheric ozone trends and attributions over East and Southeast Asia in 1995–2019: an integrated assessment using statistical methods, machine learning models, and multiple chemical transport models

Lu, Xiao ; Liu, Yiming; Su, Jiayin; Weng, Xiang; Ansari, Tabish; Zhang, Yuqiang; He, Guowen; Zhu, Yuqi; Wang, Haolin; Zeng, Ganquan; Li, Jingyu; He, Cheng; Li, Shuai; Amnuaylojaroen, Teerachai; Butler, Tim; Fan, Qi; Fan, Shaojia; Forster, Grant L.; Gao, Meng; ... mehr

Abstract:

We apply a statistical model, two machine learning models, and three chemical transport models to attribute the observed ozone increases over East and Southeast Asia (ESEA) to changes in anthropogenic emissions and climate. Despite variations in model capabilities and emission inventories, all chemical transport models agree that increases in anthropogenic emission are a primary driver of ozone increases in 1995–2019. The models attribute 53 %–59 % of the increase in tropospheric ozone burden over ESEA to changes in anthropogenic emissions, with emission within ESEA contributing by 66 %–77 %. South Asia has increasing contribution to ozone increases over ESEA. At the surface, the models attribute 69 %–75 % of the ozone increase in 1995–2019 to changes in anthropogenic emissions. Climate change also contributes substantially to the increase in summertime tropospheric (41 %–47 %) and surface ozone (25 %–31 %). We find that emission reductions in China since 2013 have led to contrasting responses in ozone levels in the troposphere (decrease) and at the surface (increase). From 2013 to 2019, the ensemble mean derived from multiple models estimate that 66 % and 56 % of the summertime surface ozone enhancement in the North China Plain and the Yangtze River Delta could be attributed to changes in anthropogenic emissions, respectively, with the remaining attributed to meteorological factors. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000183515
Veröffentlicht am 28.07.2025
Originalveröffentlichung
DOI: 10.5194/acp-25-7991-2025
Scopus
Zitationen: 6
Web of Science
Zitationen: 5
Dimensions
Zitationen: 4
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung (IMK)
Institut für Meteorologie und Klimaforschung Atmosphärische Spurengase und Fernerkundung (IMKASF)
Institut für Theoretische Informatik (ITI)
Publikationstyp Zeitschriftenaufsatz
Publikationsdatum 29.07.2025
Sprache Englisch
Identifikator ISSN: 1680-7324
KITopen-ID: 1000183515
HGF-Programm 12.11.13 (POF IV, LK 01) Long-term trends of global atmospheric composition
Weitere HGF-Programme 12.11.25 (POF IV, LK 01) Atmospheric composition and circulation changes
Erschienen in Atmospheric Chemistry and Physics
Verlag European Geosciences Union (EGU)
Band 25
Heft 14
Seiten 7991–8028
Vorab online veröffentlicht am 28.07.2025
Schlagwörter ozone, air pollution, chemical transport modeling, attribution, machine learning
Nachgewiesen in Dimensions
Web of Science
OpenAlex
Scopus
Globale Ziele für nachhaltige Entwicklung Ziel 13 – Maßnahmen zum Klimaschutz
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