Quantifying the impact of synoptic circulation patterns on ozone variability in northern China from April to October 2013–2017

<p>The characteristics of ozone variations and the impacts of synoptic and local meteorological factors in northern China were quantitatively analyzed during the warm season from 2013 to 2017 based on multi-city in situ ozone and meteorological data as well as meteorological reanalysis. The do...

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Bibliographic Details
Main Authors: J. Liu, L. Wang, M. Li, Z. Liao, Y. Sun, T. Song, W. Gao, Y. Wang, Y. Li, D. Ji, B. Hu, V.-M. Kerminen, M. Kulmala
Format: Article
Language:English
Published: Copernicus Publications 2019-11-01
Series:Atmospheric Chemistry and Physics
Online Access:https://www.atmos-chem-phys.net/19/14477/2019/acp-19-14477-2019.pdf
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Summary:<p>The characteristics of ozone variations and the impacts of synoptic and local meteorological factors in northern China were quantitatively analyzed during the warm season from 2013 to 2017 based on multi-city in situ ozone and meteorological data as well as meteorological reanalysis. The domain-averaged maximum daily 8&thinsp;h running average <span class="inline-formula">O<sub>3</sub></span> (MDA8 <span class="inline-formula">O<sub>3</sub></span>) concentration was <span class="inline-formula">122±11</span>&thinsp;<span class="inline-formula">µ</span>g&thinsp;m<span class="inline-formula"><sup>−3</sup></span>, with an increase rate of 7.88&thinsp;<span class="inline-formula">µ</span>g&thinsp;m<span class="inline-formula"><sup>−3</sup></span>&thinsp;yr<span class="inline-formula"><sup>−1</sup></span>, and the three most polluted months were closely related to the variations in the synoptic circulation patterns, which occurred in June (149&thinsp;<span class="inline-formula">µ</span>g&thinsp;m<span class="inline-formula"><sup>−3</sup></span>), May (138&thinsp;<span class="inline-formula">µ</span>g&thinsp;m<span class="inline-formula"><sup>−3</sup></span>) and July (132&thinsp;<span class="inline-formula">µ</span>g&thinsp;m<span class="inline-formula"><sup>−3</sup></span>). A total of 26 weather types (merged into five weather categories) were objectively identified using the Lamb–Jenkinson method. The highly polluted weather categories included the S–W–N directions (geostrophic wind direction diverts from south to north), low-pressure-related weather types (LP) and cyclone type, which the study area controlled by a low-pressure center (C), and the corresponding domain-averaged MDA8 <span class="inline-formula">O<sub>3</sub></span> concentrations were 122, 126 and 128&thinsp;<span class="inline-formula">µ</span>g&thinsp;m<span class="inline-formula"><sup>−3</sup></span>, respectively. Based on the frequency and intensity changes of the synoptic circulation patterns, 39.2&thinsp;% of the interannual increase in the domain-averaged <span class="inline-formula">O<sub>3</sub></span> from 2013 to 2017 was attributed to synoptic changes, and the intensity of the synoptic circulation patterns was the dominant factor. Using synoptic classification and local meteorological factors, the segmented synoptic-regression approach was established to evaluate and forecast daily ozone variability on an urban scale. The results showed that this method is practical in most cities, and the dominant factors are the maximum temperature, southerly winds, relative humidity on the previous day and on the same day, and total cloud cover. Overall, 41&thinsp;%–63&thinsp;% of the day-to-day variability in the MDA8 <span class="inline-formula">O<sub>3</sub></span> concentrations was due to local meteorological variations in most cities over northern China, except for two cities: QHD (Qinhuangdao) at 34&thinsp;% and ZZ (Zhengzhou) at 20&thinsp;%. Our quantitative exploration of the influence of both synoptic and local meteorological factors on interannual and day-to-day ozone variability will provide a scientific basis for evaluating emission reduction measures that have been implemented by the national and local governments to mitigate air pollution in northern China.</p>
ISSN:1680-7316
1680-7324