Anomaly-based synoptic analysis to identify and predict meteorological conditions of strong ozone events in North China-Reference-Cited by-同舟云学术

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Anomaly-based synoptic analysis to identify and predict meteorological conditions of strong ozone events in North China

Published:2022-06-04 Issue:10 Volume:15 Page:1699-1711
ISSN:1873-9318
Container-title:Air Quality, Atmosphere & Health
language:en
Short-container-title:Air Qual Atmos Health

Author:

Qian Weihong^ORCID,Xu Mengyang,Ai Yang

Funder

Guangdong Province Introduction of Innovative R&D Team

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Health, Toxicology and Mutagenesis,Management, Monitoring, Policy and Law,Atmospheric Science,Pollution

Link

https://link.springer.com/content/pdf/10.1007/s11869-022-01208-w.pdf

Reference37 articles.

1. Ainsworth EA, Yendrek CR, Sitch S et al (2012) The effects of tropospheric ozone on net primary productivity and implications for climate change. Annu Rev Plant Biol 63:637–661. https://doi.org/10.1146/annurev-arplant-042110-103829

2. Chen Y, Hu Q, Yang YM et al (2017) Anomaly based analysis of extreme heat waves in eastern China during 1981–2013. Int J Climatol 37:509–523. https://doi.org/10.1002/joc.4724

3. Fleming ZL, Doherty RM, von Schneidemesser E, et al (2018) Tropospheric ozone assessment report: present-day ozone distribution and trends relevant to human health. Elementa-Sci Anthrop 6:12. https://doi.org/10.1525/elementa.273

4. Gong C, Liao H (2019) A typical weather pattern for ozone pollution events in North China. Atmos Chem Phys 19:13725–13740. https://doi.org/10.5194/acp-19-13725-2019

5. Grumm RH, Hart R (2001) Standardized anomalies applied to significant cold season weather events: preliminary findings. Weather Forecast 16:736–754. https://doi.org/10.1175/1520-0434(2001)016%3c0736:Saatsc%3e2.0.Co;2

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