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Increased night-time oxidation over China despite widespread decrease across the globe

Nature Geoscience volume 16, pages 217–223 (2023)Cite this article

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Abstract

Nitrogen oxides (NOx = NO + NO2) emitted from combustion and natural sources are reactive gases that regulate the composition of Earth’s atmosphere. Nocturnal oxidation driven by nitrate radicals is an important but poorly understood process in atmospheric chemistry, affecting the lifetimes of NOx and ozone and particulate pollution levels. Understanding the trends of nitrate radicals is important to formulating effective pollution mitigation strategies and understanding the influence of NOx on climate. Here we analyse publicly available monitoring data on NOx and ozone to assess production rates and trends of surface nitrate radicals from 2014 to 2021 across the globe. We show that nitrate radicals have undergone strong increases in China during 2014–2019 but exhibited modest decreases in the United States and the European Union. Accelerated night-time oxidation has shortened the lifetime of summer NOx in China by 30% during 2014–2019. This change will strongly affect ozone formation and has policy implications for the joint control of ozone and fine particulate pollution.

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Fig. 1: Observed level and trend of nocturnal PNO3 in the warm season.
Fig. 2: The annual mean diurnal cycle of PNO3 by region.
Fig. 3: Conceptual framework on the dependence of PNO3 on NOx emission.
Fig. 4: The warm-season trends of nocturnal PNO3, NO2 and O3 from 1980 to 2021.

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Data availability

The data are available via figshare (https://doi.org/10.6084/m9.figshare.20290587.v4). The hourly ground-based observations of NO2 and O3 over China, the United States, the European Union and India are archived at https://quotsoft.net/air/, https://www.epa.gov/outdoor-air-quality-data, https://discomap.eea.europa.eu/map/fme/AirQualityExport.htm and https://app.cpcbccr.com/ccr/, respectively. The hourly 2 m air temperature MERRA-2 reanalysis data are from https://doi.org/10.5067/VJAFPLI1CSIV. The box-model simulation dataset is available via figshare (https://doi.org/10.6084/m9.figshare.21268014). Source data are provided with this paper.

Code availability

All figures in this article are produced by the IDL (Interactive Data Language version 8.3) and python, and the source codes can be obtained upon request to the corresponding authors.

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Acknowledgements

Haichao Wang received financial support from the National Natural Science Foundation of China (grant 42175111). K.L. received financial support from the National Natural Science Foundation of China (grants 22221004, 21976006, 91844301). K.L. received financial support from the Beijing Municipal Natural Science Foundation for Distinguished Young Scholars (JQ19031). K.L. received financial support from the National Research Program for Key Issue in Air Pollution Control (2019YFC0214800). Haichao Wang received financial support from the National State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex (grant CX2020080578). Y.J.T. received financial support from National Natural Science Foundation of China (42175118) and Guangdong Basic and Applied Basic Research Foundation (2022A1515010852).

Author information

Author notes

  1. These authors contributed equally: Haichao Wang, Haolin Wang, Xiao Lu.

Authors and Affiliations

  1. School of Atmospheric Sciences, Sun Yat-Sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China

    Haichao Wang, Haolin Wang, Xiao Lu & Shaojia Fan

  2. State Key Joint Laboratory of Environmental Simulation and Pollution Control, The State Environmental Protection Key Laboratory of Atmospheric Ozone Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, China

    Haichao Wang, Keding Lu & Yuanhang Zhang

  3. Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Key Laboratory of Tropical Atmosphere-Ocean System (Sun Yat-sen University), Ministry of Education, Zhuhai, China

    Haichao Wang, Haolin Wang, Xiao Lu & Shaojia Fan

  4. Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing, China

    Lin Zhang

  5. School of Marine Sciences, Sun Yat-sen University, Zhuhai, China

    Yee Jun Tham

  6. School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, UK

    Zongbo Shi

  7. Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, CO, USA

    Kenneth Aikin

  8. NOAA Chemical Sciences Laboratory, Boulder, CO, USA

    Kenneth Aikin & Steven S. Brown

  9. Department of Chemistry, University of Colorado, Boulder, CO, USA

    Steven S. Brown

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Contributions

Haichao Wang, K.L., S.S.B. and Y.Z. designed the study. Haichao Wang, K.L., Haolin Wang, K.A. and X.L. analysed the data and wrote the paper with input from L.Z., Y.J.T., Z.S. and S.F.

Corresponding authors

Correspondence to Keding Lu, Steven S. Brown or Yuanhang Zhang.

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Extended data

Extended Data Fig. 1 Average nocturnal O3 and NO2 in 2018–2019 and 2020–2021 in warm season.

Observed level and trend of nocturnal O3 and NO2 in the warm season (April–September). a,b, Average nocturnal O3 (a) and NO2 (b) in warm season during 2018–2019. c,d, Average nocturnal O3 (c) and NO2 (d) in warm season during 2020–2021. The average ± standard deviation result in China, the United States, the European Union and India are labelled out in the left in each panel. Basemap reproduced from ref. 52 under a Creative Commons license CC BY 4.0.

Source data

Extended Data Fig. 2 Histograms of the change rates of PNO3 during 2014–2019.

Site number histograms of the change rates of PNO3 during 2014–2019 in different seasons and regions. a,b, Results of China, the European Union and the United States in warm (a) and cold (b) seasons. c,d, Same as a and b but for four city clusters in China.

Source data

Extended Data Fig. 3 Observed level and trend of nocturnal nitrate radical production rate (PNO3) in the cold season (April–September).

Same as Fig. 1 but in cold season. Basemap reproduced from ref. 52 under a Creative Commons license CC BY 4.0.

Source data

Extended Data Fig. 4 Average nocturnal O3 and NO2 in 2018–2019 and 2020–2021 in cold season.

Same as Extended Data Fig. 1. but for cold season. Basemap reproduced from ref. 52 under a Creative Commons license CC BY 4.0.

Source data

Extended Data Fig. 5 Annual nocturnal lifetime of NO2.

The box whisker of annual nocturnal lifetime of NO2 in warm. (a), and cold season. (b), in the four regions. More details of the data are listed in Supplementary Table 1.

Source data

Extended Data Fig. 6 The annual trend of nocturnal PNO3, NO2 and O3 from 1980 to 2021.

Same as Fig. 4 but for cold season.

Source data

Extended Data Fig. 7 The nocturnal dependence of PNO3 on the NOx emission.

The nocturnal NO3 production rate as functions of the NOx emission at different VOC level. The dots in different color represent the average condition in the five regions (the United States, the European Union, China and India in 2018–2019 and LA in 1980).

Source data

Extended Data Table 1 The PNO3, O3, NO2, during 2018–2019
Full size table
Extended Data Table 2 The temperature and the reaction rate constant of NO2 and O3 during 2018–2019
Full size table
Extended Data Table 3 The trend PNO3 and sites distribution in each region during 2014–2019
Full size table

Supplementary information

Supplementary information

Supplementary Figs. 1–3 and Table 1.

Source data

Source Data Fig. 1

Observed level and trend of nocturnal PNO3 in the warm season (April–September).

Source Data Fig. 2

The diurnal cycle of PNO3.

Source Data Fig. 3

The modelled dependence of nocturnal O3, Ox and NO3 production rate on the NOx emission at a fixed VOC level.

Source Data Fig. 4

The cold-season trends of nocturnal PNO3, NO2 and O3 from 1980 to 2021.

Source Data Extended Data Fig. 1

Observed level and trend of nocturnal O3 and NO2 in the warm season (April–September).

Source Data Extended Data Fig. 2

Site number histograms of the change rates of PNO3 during 2014–2019 in different seasons and regions

Source Data Extended Data Fig. 3

Observed level and trend of nocturnal PNO3 in the warm season (April–September) during 2014–2019.

Source Data Extended Data Fig. 4

Observed level and trend of nocturnal O3 and NO2 in the cold season (October–March)

Source Data Extended Data Fig. 5

The box-and-whisker data of annual nocturnal lifetime of NO2.

Source Data Extended Data Fig. 6

The warm-season trends of nocturnal PNO3, NO2 and O3 from 1980 to 2021.

Source Data Extended Data Fig. 7

The modelled nocturnal NO3 production rates as functions of the NOx emission at different VOC levels.

Source Data Extended Data Table 1

PNO3, O3 and NO2 in each region during warm and cold seasons during 2018–2019.

Source Data Extended Data Table 2

Temperature and the reaction rate constant of NO2 and O3 in each region during warm and cold seasons during 2018–2019.

Source Data Extended Data Table 3

The trend of PNO3 and sites distribution in each region during warm and cold seasons during 2014–2019.

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Wang, H., Wang, H., Lu, X. et al. Increased night-time oxidation over China despite widespread decrease across the globe. Nat. Geosci. 16, 217–223 (2023). https://doi.org/10.1038/s41561-022-01122-x

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