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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Volume 11, issue 4
Atmos. Meas. Tech., 11, 2239-2255, 2018
https://doi.org/10.5194/amt-11-2239-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Atmos. Meas. Tech., 11, 2239-2255, 2018
https://doi.org/10.5194/amt-11-2239-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 19 Apr 2018

Research article | 19 Apr 2018

MAX-DOAS NO2 observations over Guangzhou, China; ground-based and satellite comparisons

Theano Drosoglou1, Maria Elissavet Koukouli1, Natalia Kouremeti2, Alkiviadis F. Bais1, Irene Zyrichidou1, Dimitris Balis1, Ronald J. van der A3,4, Jin Xu5, and Ang Li5 Theano Drosoglou et al.
  • 1Laboratory of Atmospheric Physics, Aristotle University of Thessaloniki, Thessaloniki, Greece
  • 2Physikalisch-Meteorologisches Observatorium Davos, World Radiation Center, Davos, Switzerland
  • 3R&D Satellite Observations, Royal Netherlands Meteorological Institute (KNMI), De Bilt, the Netherlands
  • 4School of Atmospheric Physics, Nanjing University of Information Sciences and Technology, Nanjing, China
  • 5Anhui Institute of Optics and Fine Mechanics Academy of Sciences (AIOFM), Chinese Academy of Sciences (CAS), Hefei, China

Abstract. In this study, the tropospheric NO2 vertical column density (VCD) over an urban site in Guangzhou megacity in China is investigated by means of MAX-DOAS measurements during a campaign from late March 2015 to mid-March 2016. A MAX-DOAS system was deployed at the Guangzhou Institute of Geochemistry of the Chinese Academy of Sciences and operated there for about 1 year, during the spring and summer months. The tropospheric NO2 VCDs retrieved by the MAX-DOAS are presented and compared with space-borne observations from GOME-2/MetOp-A, GOME-2/MetOp-B and OMI/Aura satellite sensors. The comparisons reveal good agreement between satellite and MAX-DOAS observations over Guangzhou, with correlation coefficients ranging between 0.795 for GOME-2B and 0.996 for OMI. However, the tropospheric NO2 loadings are underestimated by the satellite sensors on average by 25.1, 10.3 and 5.7%, respectively, for OMI, GOME-2A and GOME-2B. Our results indicate that GOME-2B retrievals are closer to those of the MAX-DOAS instrument due to the lower tropospheric NO2 concentrations during the days with valid GOME-2B observations. In addition, the effect of the main coincidence criteria is investigated, namely the cloud fraction (CF), the distance (d) between the satellite pixel center and the ground-based measurement site, as well as the time period within which the MAX-DOAS data are averaged around the satellite overpass time. The effect of CF and time window criteria is more profound on the selection of OMI overpass data, probably due to its smaller pixel size. The available data pairs are reduced to half and about one-third for CF ≤ 0.3 and CF ≤ 0.2, respectively, while, compared to larger CF thresholds, the correlation coefficient is improved to 0.996 from about 0.86, the slope value is very close to unity ( ∼ 0.98) and the mean satellite underestimation is reduced to about half (from  ∼ 7 to  ∼ 3.5 × 1015moleculescm−2). On the other hand, the distance criterion affects mostly GOME-2B data selection, because GOME-2B pixels are quite evenly distributed among the different radii used in the sensitivity test. More specifically, the number of collocations is notably reduced when stricter radius limits are applied, the r value is improved from 0.795 (d ≤ 50km) to 0.953 (d ≤ 20km), and the absolute mean bias decreases about 6 times for d ≤ 30km compared to the reference case (d ≤ 50km).

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A diurnal pattern of tropospheric NO2 with two maxima around late morning and late afternoon is revealed, reflecting high anthropogenic emissions, and a minimum at noon, due to photochemical destruction of tropospheric NO2. GOME-2B shows the smallest underestimation despite its large pixel size. The distance between the measurement location and the satellite pixel center affects mostly GOME-2B data selection. The effect of clouds is more profound on the selection of OMI overpass data.
A diurnal pattern of tropospheric NO2 with two maxima around late morning and late afternoon is...
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