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Comparison and validation of band residual difference algorithm and principal component analysis algorithm for retrievals of atmospheric SO2 columns from satellite observations

Yan Huan-Huan Li Xiao-Jing Zhang Xing-Ying Wang Wei-He Chen Liang-Fu Zhang Mei-Gen Xu Jin

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Comparison and validation of band residual difference algorithm and principal component analysis algorithm for retrievals of atmospheric SO2 columns from satellite observations

Yan Huan-Huan, Li Xiao-Jing, Zhang Xing-Ying, Wang Wei-He, Chen Liang-Fu, Zhang Mei-Gen, Xu Jin
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  • Remote sensing technology provides an unprecedented tool for the continuous and real-time monitoring of atmospheric SO2 from volcanic eruption and anthropogenic emission. The Global Ozone Monitoring Experiment (GOME), SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY), and Ozone Monitoring Instrument (OMI) have high SO2 monitoring capability. The OMI, which was launched on the EOS/Aura platform in July 2004, has the same hyperspectral measurements as the GOME and SCIAMACHY, but offers the improved spatial resolution at nadir (1324 km2) and daily global coverage for short-lifetime SO2. For OMI operational SO2 planetary boundary layer (PBL) retrieval, the previous band residual difference (BRD) algorithm has been replaced by principal component analysis (PCA) algorithm, which effectively reduces the systematic biases in SO2 column retrievals. However, there are few studies on the evaluations and validations of PCA SO2 retrievals over China, and the long-term comparisons with BRD SO2 retrievals also need to be conducted. In this study, the accuracies of PCA and BRD SO2 retrievals are validated by using ground-based multi axis differential optical absorption spectroscopy (MAX-DOAS) located in Beijing, and regional atmospheric modeling system, community multi-scale air quality (RAMS-CMAQ) modeling system model which can simulate the vertical distribution of atmospheric SO2. Moreover, BRD and PCA SO2 retrievals from oceanic area, eastern China and Reunion volcanic eruption are compared to find the long-term trend and spatiotemporal differences between SO2 columns. Finally, the uncertainty of SO2 retrieval, caused by measurement errors, band selection and input parameter errors in radiative transfer model, are analysed to understand the limitations of BRD and PCA algorithms. Results show that both PCA and BRD SO2 retrievals over Beijing are lower than ground-based MAX-DOAS measurements of SO2. PCA and BRD SO2 retrievals over eastern China are lower than the simulated SO2 columns from RAMS-CMAQ in winter 2008, but in July and August BRD SO2 columns are higher than RAMS-CMAQ simulations. The values of SO2 columns from BRD over China are more consistent with those from ground-based MAX-DOAS and RAMS-CMAQ model than from PCA. Although PCA algorithm effectively reduces the noise in SO2 column retrieval, SO2 columns from PCA over China are lower than those from BRD. For oceanic area where SO2 amount is nearly zero, the standard deviation of PCA results is lower than that of BRD, but the absolute value of averaged PCA SO2 column is larger than that of BRD. In the case of Reunion volcanic eruption with SO2 columns larger than 25 DU, the BRD SO2 columns are lower than PCA retrievals. Meanwhile, with the increase of SO2 column, the difference between BRD and PCA SO2 retrievals increases. Detailed uncertainty analysis shows the influences of measurement errors, band selection and inputs of radiative transfer model on the retrieval results. This study is important for developing the retrieval algorithm, and can also improve the application of OMI SO2 products.
      Corresponding author: Li Xiao-Jing, lixiaoj@cma.gov.cn
    • Funds: Project supported by the Young Science Fund from National Satellite Meteorological Center, High-resolution Earth Observation System, China (Grant No. E310/1112), the Special Scientific Research Fund of Meteorological Public Welfare Profession of China (Grant No. GYHY201106045), Partnership with China on Space Data (PANDA) (Grant No. 606719), National Natural Science Foundation of China (Grant No. 41501413).
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  • [1]

    Myhre G, Stordal F, Berglen T F, Sundet J K, Isaksen I S A 2004 J. Atmos. Sci. 61 485

    [2]

    Benkovitz C M, Schwartz S E, Jensen M P, Miller M A 2006 Atmos. Chem. Phys. 6 4723

    [3]

    Jernelov A 1983 Ambio 12 362

    [4]

    Larssen T, Lydersen E, Tang D G, He Y, Gao J X, Liu H Y, Duan L, Seip H M, Vogt R D, Mulder J, Shao M, Wang Y H, Shang H, Zhang X S, Solberg S, Aas W, Okland T, Eilertsen O, Angell V, Liu Q R, Zhao D W, Xiang R J, Xiao J S, Luo J H 2006 Environ. Sci. Technol. 40 418

    [5]

    Zhao D, Sun B 1986 Ambio 15 2

    [6]

    Haines A 2003 Int. J. Epidemiol. 32 321

    [7]

    Fishman J, Bowman K W, Burrows J P, Richter A, Chance K V, Edwards D P, Martin R V, Morris G A, Pierce R B, Ziemke J R, Al-Saadi J A, Creilson J K, Schaack T K, Thompson A M 2008 B. Am. Meteorol. Soc. 89 805

    [8]

    Martin R V 2008 Atmos. Environ. 42 7823

    [9]

    Burrows J P, Weber M, Buchwitz M, Rozanov V, Ladstatter-Weissenmayer A, Richter A, DeBeek R, Hoogen R, Bramstedt K, Eichmann K U, Eisinger M 1999 J. Atmos. Sci. 56 151

    [10]

    Eisinger M, Burrows J P 1998 Geophys. Res. Lett. 25 4177

    [11]

    Gottwald M, Bovensmann H, Lichtenberg G, Noel S, von Bargen A, Slijkhuis S, Piters A, Hoogeveen R, von Savigny C, Buchwitz M 2006 Sciamachy, Monitoring the Changing Earth's Atmosphere (Germany: DLR) pp31-42

    [12]

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    [13]

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    [14]

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    [15]

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    [16]

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    [17]

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    [18]

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    [19]

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    [21]

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    [27]

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    [28]

    Ialongo I, Hakkarainen J, Kivi R, Anttila P, Krotkov N, Yang K, Li C, Tukiainen S, Hassinen S, Tamminen J 2015 Atmos. Meas. Tech. 8 2279

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    Zhang M, Gao L, Ge C, Xu Y 2007 Tellus B 59 372

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    Lu Z, Zhang Q, Streets D G 2011 Atmos. Chem. Phys. 11 9839

    [51]

    Chin M, Savoie D L, Huebert B J, Bandy A R, Thornton D C, Bates T S, Quinn P K, Saltzman E S, De Bruyn W J 2000 J. Geophys. Res. Atmos. 105 24689

    [52]

    Wang Y S, Yao L, Wang L L, Liu Z R, Ji D S, Tang G Q, Zhang J K, Sun Y, Hu B, Xin J Y 2014 Sci. China: Earth Sci. 44 15 (in Chinese) [王跃思, 姚利, 王莉莉, 刘子锐, 吉东生, 唐贵谦, 张军科, 孙扬, 胡波, 辛金元 2014 中国科学: 地球科学 44 15]

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  • Abstract views:  6510
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Publishing process
  • Received Date:  20 October 2015
  • Accepted Date:  25 December 2015
  • Published Online:  05 April 2016

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