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Low-NO atmospheric oxidation pathways in a polluted megacity

  • Mike J. Newland*
  • , Daniel J. Bryant
  • , Rachel E. Dunmore
  • , Thomas J. Bannan
  • , W. Joe
  • , Ben Langford
  • , James R. Hopkins
  • , Freya A. Squires
  • , William Dixon
  • , William S. Drysdale
  • , Peter D. Ivatt
  • , Mathew J. Evans
  • , Peter M. Edwards
  • , Lisa K. Whalley
  • , Dwayne E. Heard
  • , Eloise J. Slater
  • , Robert Woodward-Massey
  • , Chunxiang Ye
  • , Archit Mehra
  • , Stephen D. Worrall
  • Asan Bacak, Hugh Coe, Carl J. Percival, C. Nicholas Hewitt, James D. Lee, Tianqu Cui, Jason D. Surratt, Xinming Wang, Alastair C. Lewis, Andrew R. Rickard, Jacqueline F. Hamilton
*Corresponding author for this work
  • University of York
  • University of Manchester
  • Lancaster Environment Centre
  • UK Centre for Ecology & Hydrology (UKCEH)
  • University of Leeds
  • Peking University People's Hospital
  • California Institute of Technology
  • University of North Carolina
  • Guangzhou Institute of Geochemistry Chinese Academy of Sciences

Research output: Contribution to journal › Article › peer-review

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Abstract

The impact of emissions of volatile organic compounds (VOCs) to the atmosphere on the production of secondary pollutants, such as ozone and secondary organic aerosol (SOA), is mediated by the concentration of nitric oxide (NO). Polluted urban atmospheres are typically considered to be "high-NO"environments, while remote regions such as rainforests, with minimal anthropogenic influences, are considered to be "low NO". However, our observations from central Beijing show that this simplistic separation of regimes is flawed. Despite being in one of the largest megacities in the world, we observe formation of gas- and aerosol-phase oxidation products usually associated with low-NO "rainforest-like"atmospheric oxidation pathways during the afternoon, caused by extreme suppression of NO concentrations at this time. Box model calculations suggest that during the morning high-NO chemistry predominates (95 %) but in the afternoon low-NO chemistry plays a greater role (30 %). Current emissions inventories are applied in the GEOS-Chem model which shows that such models, when run at the regional scale, fail to accurately predict such an extreme diurnal cycle in the NO concentration. With increasing global emphasis on reducing air pollution, it is crucial for the modelling tools used to develop urban air quality policy to be able to accurately represent such extreme diurnal variations in NO to accurately predict the formation of pollutants such as SOA and ozone.

Original languageEnglish
Pages (from-to)1613-1625
Number of pages13
JournalAtmospheric Chemistry and Physics
Volume21
Issue number3
DOIs
Publication statusPublished - 8 Feb 2021

Bibliographical note

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Funding: This research has been supported by the Natural Environment Research Council and the Newton Fund and
Medical Research Council in the UK and by the National Natural Science Foundation of China (grant nos. NE/N007190/1 and
NE/N006917/1)

Funding

Financial support. This research has been supported by the Nat- Acknowledgements. We acknowledge the support from Pingqing Fu, Zifa Wang, Jie Li, and Yele Sun from the IAP for hosting the APHH-Beijing campaign at the IAP. We thank Zongbo Shi, Roy Harrison, Tuan Vu, and Bill Bloss from the University of Birmingham; Siyao Yue, Liangfang Wei, Hong Ren, Qiaorong Xie, Wanyu Zhao, Linjie Li, Ping Li, Shengjie Hou, and Qingqing Wang from the IAP; Kebin He and Xiaoting Cheng from Tsinghua University; and James Allan from the University of Manchester for providing logistic and scientific support for the field campaigns. Peter Ivatt acknowledges funding from NCAS through one of its Air Pollution and Human Health studentships. Daniel Bryant, William Dixon, William Drysdale, Freya Squires, and Eloise Slater acknowledge the NERC SPHERES Doctoral Training Partnership (DTP) for studentships.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities

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