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Cited by 333Atmospheric chemistry and aerosolsAtmospheric Ozone and ClimateAtmospheric and Environmental Gas Dynamics

The DOI matches its Crossref record; 49 of the 52 references it cites were found in a registry or an index.

Significant increase of surface ozone at a rural site, north of eastern China

Open access
Ma, Zhiqiang, Xu, Jing, Quan, Weijun, Zhang, Ziyin, Lin, Weili, Xu, Xiaobin·2016·Atmospheric chemistry and physics
DOI 10.5194/acp-16-3969-2016

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Abstract

Abstract. Ozone pollution has become one of the top environmental concerns in eastern China. Quantifying temporal trend of surface ozone concentrations is very meaningful to assess the impacts of the anthropogenic precursor reductions and the effects of emission control strategies. The level of surface ozone is impacted by both emissions of precursors and meteorological conditions. In order to examine the variation trend of ozone from 2003 to 2015 in Shangdianzi regional atmosphere background station, the modified KZ filter method was performed in this study to remove the influence of meteorological fluctuations on ozone concentrations. Results reveal that the short-term component, seasonal component and long-term component of ozone account for 36.4, 57.6 and 2.2 % of the total variance, respectively. The long-term trend shows that the surface daily maximum 8-h O3 has undergone a significant increase during 2003–2015, with a rate of 1.1 ppb yr−1. We find that the increase was completely resulted from the change of the emissions when the influence of the meteorological factors was eliminated. Furthermore, the variation of NO2 indicated that VOCs seemed to play more important role in the increase trend of the surface ozone.

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Crossref · 10.5194/acp-16-3969-2016

Cites

49 of 49 references verified0 citation errors · 0 not checkable

Statistics

Figures

Figure 1 Percentile-box plot of yearly statistics of MDA8 values of ozone at SDZ, in the period of 2004-2015. Boxes depict interquartile range and median; the squares depict the mean; whiskers depict 10th and 90th percentile; dots depict maximum values.
Figure 1 Percentile-box plot of yearly statistics of MDA8 values of ozone at SDZ, in the period of 2004-2015. Boxes depict interquartile range and median; the squares depict the mean; whiskers depict 10th and 90th percentile; dots depict maximum values.CC-BY · From the PDF
Figure 2 Separated time series of MDA8 values of ozone at SDZ: (a) the original data; (b) the short-term component, W.t/ ; (c) the seasonal component, S.t/ ; (d) the long-term component, e.t/ .
Figure 2 Separated time series of MDA8 values of ozone at SDZ: (a) the original data; (b) the short-term component, W.t/ ; (c) the seasonal component, S.t/ ; (d) the long-term component, e.t/ .CC-BY · From the PDF
Figure 3 Q -Q plot of the short-term component W.t/ for ozone.
Figure 3 Q -Q plot of the short-term component W.t/ for ozone.CC-BY · From the PDF
Figure 4 Separated time series of daily mean values of temperature at SDZ: (a) the original data; (b) the short-term component, W.t/ ; (c) the seasonal component, S.t/ ; (d) the long-term component, e.t/ .
Figure 4 Separated time series of daily mean values of temperature at SDZ: (a) the original data; (b) the short-term component, W.t/ ; (c) the seasonal component, S.t/ ; (d) the long-term component, e.t/ .CC-BY · From the PDF
Figure 5 Results of the daily mean temperature and the MDA8 value of ozone after the application of the KZ 15 ; 5 filter to the original time series. The results indicate the sum of the seasonal and long-term components.
Figure 5 Results of the daily mean temperature and the MDA8 value of ozone after the application of the KZ 15 ; 5 filter to the original time series. The results indicate the sum of the seasonal and long-term components.CC-BY · From the PDF
Figure 6 Linear regression fit on the filtered daily maxima of temperature and ozone. Temperature data are lagged by 17 days to ozone data.
Figure 6 Linear regression fit on the filtered daily maxima of temperature and ozone. Temperature data are lagged by 17 days to ozone data.CC-BY · From the PDF
Figure 7 Time series of the noise-free and temperatureindependent ozone. The red line is a linear fit and the blue lines are the 95 % confidence prediction band.
Figure 7 Time series of the noise-free and temperatureindependent ozone. The red line is a linear fit and the blue lines are the 95 % confidence prediction band.CC-BY · From the PDF
Figure 8 Long-term trends of NO 2 and the MDA8 ozone value calculated by KZ 365 ; 3 :
Figure 8 Long-term trends of NO 2 and the MDA8 ozone value calculated by KZ 365 ; 3 :CC-BY · From the PDF

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Citations

Cites

Show all 52 references

Research works printed but not linked: 4

  1. Eskridge, R. E., Ku, J. Y., Rao, S. T., Porter, P. S., and Zurbenko, I. G.: Separating Different Scales of Motion in Time Series of Meteorological Variables, B. Am. Meteorol. Soc., 78, 1473–1483, 10.1175/1520-0477(1997)0782.0.CO;2, 1997. · DOI
  2. IPCC: Climate Change 2013 – The Physical Science Basis, Cambridge University Press, Cambridge, 1552 pp., 2013.
  3. NRC (National Research Council): Rethinking the Ozone Problem in Urban and Regional Air Pollution, National Academy Press, Washington, D.C., 1991.
  4. Penkett, S. A.: Indications and causes of ozone increase in the troposphere, in: Rowland, F. S. and Isaksen, I. S. A., The Changing Atmosphere, J. Wiley&Sons, p. 91, 1988.

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Metadata

Authors
Ma, Z., Xu, J., Quan, W., Zhang, Z., Lin, W., & Xu, X.
Affiliations
  • China Meteorological Administration (CN)
  • Chinese Academy of Meteorological Sciences (CN)
Corresponding author
Lin, Weili
ORCID
Venue
Atmospheric chemistry and physics
Publisher
Copernicus GmbH
Published
2016-03-24
Volume
16
Issue
6
Pages
3969-3977
ISSN
  • 1680-7316 (ISSN-L)
  • 1680-7324
DOI
10.5194/acp-16-3969-2016
OpenAlex
W2304410378
Cited by
332
References
52
Citations by year
2026: 6 · 2025: 21 · 2024: 30 · 2023: 42 · 2022: 52 · 2021: 50 · 2020: 49 · 2019: 40 · 2018: 21 · 2017: 16 · 2016: 5
FWCI
16.68
Type
journal article
Language
en
Open access
Licence
Locations
  • Atmospheric chemistry and physics (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • National Natural Science Foundation of China (41475135)
  • Natural Science Foundation of Beijing Municipality (8132025, 8152018)
Topics
  • Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Atmospheric chemistry and aerosols
  • Physical Sciences › Earth and Planetary Sciences › Atmospheric Science › Atmospheric Ozone and Climate
  • Physical Sciences › Environmental Science › Global and Planetary Change › Atmospheric and Environmental Gas Dynamics
Keywords
surface ozone, ozone trends, North China Plain, VOC emissions, NO2, seasonal ozone variation

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