Nighttime aerosol optical depth retrievals from VIIRS day/night band data

  • role: First author第一作者
  • Affiliation:

    Key Laboratory of Photoelectric Imaging Technology and System of Ministry of Education , School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China

  • Email:871331483@qq.com
  • Introduction:E-mail 871331483@qq.com
JIANG Mengdie1,  
  • role: Corresponding author通信作者
  • Affiliation:

    National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081, China

    Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, China Meteorological Administration, Beijing 100081, China

  • Email:chenlin@cma.gov.cn
  • Introduction:E-mail chenlin@cma.gov.cn
CHEN Lin23*,  
  • Affiliation:

    Key Laboratory of Photoelectric Imaging Technology and System of Ministry of Education , School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China

HE Yuqing1,  
  • Affiliation:

    National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081, China

    Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, China Meteorological Administration, Beijing 100081, China

HU Xiuqing23,  
  • Affiliation:

    Key Laboratory of Photoelectric Imaging Technology and System of Ministry of Education , School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China

LIU Mingqi1,  
  • Affiliation:

    National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081, China

    Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, China Meteorological Administration, Beijing 100081, China

ZHANG Peng23

реферат

Aerosol has an extensive impact on Earth’s climate and ecosystems and thus harmful to human health. The distribution of atmospheric aerosols has diurnal variation, and nighttime aerosol concentrations are higher than those during the day. Therefore, the accurate monitoring of AOD at night is significant but challenging. The Visible/Infrared Imager/Radiometer Suite (VIIRS) of Suomi National Polar-orbiting Partnership has a Day Night Band (DNB), which can observe the city light overnight. The artificial night light observed by the DNB of VIIRS reflects the extinction effect of the atmosphere and it is helpful in obtaining the nighttime AOD.To monitor the nighttime AOD, this study obtained the nighttime AOD on the basis of the theory of atmospheric radiation transmission. First, moonless and cloudless DNB data were selected, and the artificial lights during the crescent period were obtained by multi-day DNB data fusion. Second, the nighttime AOD was retrieved based on the extinction effect of aerosol on artificial lights. Finally, the obtained AOD is compared with the AOD from the CE318 and AQI indices from the environmental quality monitoring station to verify the feasibility of the retrieval method.This study focused on the nighttime AOD in North China from March 2016 to February 2017. The artificial lights of North China from four seasons were obtained, indicating that the major cities, especially the JingJinJi urban agglomeration, are very prominent in the artificial lights distribution map, and the traffic network between cities is clearly visible. Meanwhile, the nighttime AOD distribution during two heavily polluted weather processes in July and October 2016 was retrieved. The retrieval results indicate that the nighttime aerosols in North China are mainly distributed in the JingJinJi region and the provincial capital, which have developed industries and a dense population. Moreover, the retrieved and observed AODs are consistent, with an agreement index of up to 0.962, indicating that the retrieval study achieved good results.This study demonstrates the potential of satellite twilight data in monitoring the spatial distribution of urban pollution at night. The distribution characteristics of nighttime urban lights and aerosols are also provided, enriching the understanding of the temporal and spatial distribution of aerosols at night.

ключеви́че слова́

nighttime aerosol;Optical depth;NPP VIIRS DNB;city lights;remote sensing retrieval

References

  1. 1.
    Che H, Zhang X Y, Xia X, Goloub P, Holben B, Zhao H, Wang Y, Zhang X C, Wang H, Blarel L, Damiri B, Zhang R, Deng X, Ma Y, Wang T, Geng F, Qi B, Zhu J, Yu J, Chen Q and Shi G. 2015. Ground-based aerosol climatology of china: aerosol optical depths from the china aerosol remote sensing network (CARSNET) 2002-2013. Atmospheric Chemistry and Physics, 15(13): 7619-7652
  2. 2.
    Chen C, Li Z Q, Hou W Z, Li D H and Zhang Y H. 2015. Dynamic model in retrieving aerosol optical depth from polarimetric measurements of PARASOL. Journal of Remote Sensing, 19(1): 25-33
  3. 3.
    Gao L, Zhang L Y, Li J, Chen L, Sun L and Li X J. 2014. Retrieval of atmospheric aerosol optical depth over land from AVHRR. Journal of Applied Meteorological Science, 25(1): 42-51
  4. 4.
    Ge B Y, Yang L K, Chen X F, Li Z Q, Mei X D and Liu L. 2018. Study on aerosol optical depth retrieval over land from Himawari-8 data based on dark target method. Journal of Remote Sensing, 22(1): 38-50
  5. 5.
    Johnson R S, Zhang J, Hyer E J, Miller S D and Reid J S. 2013. Preliminary investigations toward nighttime aerosol optical depth. Atmospheric Measurement Techniques Discussions, 6(5): 1245-1255
  6. 6.
    Kikuchi M, Murakami H, Suzuki K, Nagao T M and Higurashi A. 2018. Improved hourly estimates of aerosol optical thickness using spatiotemporal variability derived from himawari-8 geostationary satellite. IEEE Transactions on Geoscience and Remote Sensing, 56(6): 3442-3455
  7. 7.
    Li C C, Mao J T, Liu Q H, Chen J Z, Yuan Z B, Liu X Y, Zhu A H and Liu G Q. 2003. Study of distribution and the seasonal variation characteristic of aerosol optical thickness using MODIS in the east of China. Chinese Science Bulletin, 48(19): 2094-2100
  8. 8.
    Li D H, Li Z Q, Lv Y, Zhang Y, Li K T and. Xu H. 2015. Determination of nocturnal aerosol properties from a combination of lunar photometer and lidar observations//Proceedings of SPIE 9640, Remote Sensing of Clouds and the Atmosphere XX. Toulouse, France: SPIE: 96400W
  9. 9.
    Li X J, Liu Y J, Qiu H and Zhang Y X. 2003. Retrieval method for optical thickness of aerosols over Beijing and its vicinity by using the MODIS data. Acta Meteorologica Sinica, 61(5):581-592
  10. 10.
    Li Z Q, Xie Y S, Zhang Y, Li L, Xu H, Li K T and Li D H. 2019. Advance in the remote sensing of atmospheric aerosol composition. Journal of Remote Sensing, 23(3): 359-373
  11. 11.
    Li Z Q, Xu H, Li K T, Li D H, Xie Y S, Li L, Zhang Y, Gu X F, Zhao W, Tian Q J, Deng R R, Su X L, Huang B, Qiao Y L, Cui W Y, Hu Y, Gong C L, Wang Y Q, Wang X F, Wang J P, Du W B, Pan Z Q, Li Z Z and Bu D. 2018. Comprehensive study of optical, physical, chemical, and radiative properties of total columnar atmospheric aerosols over China: an overview of sun–sky radiometer observation Network (SONET) measurements. Bulletin of the American Meteorological Society, 99(4): 739-755
  12. 12.
    McHardy T M, Zhang J, Reid J S, Miller S D, Hyer E J and Kuehn R E. 2015. An improved method for retrieving nighttime aerosol optical thickness from the VIIRS Day/Night Band. Atmospheric Measurement Techniques, 8(11): 4773-4783
  13. 13.
    Su C L, Su L, Chen L F, Jia S L, Liu C and Yu C. 2015. Retrieval of aerosol optical depth using NPP VIIRS data. Journal of Remote Sensing, 19(6): 977-982
  14. 14.
    Wang W S. 2007. Coefficient of variation—A simple and useful indicator to measure the degree of dispersion. China Statistics, (6): 41-42
  15. 15.
    Xia L, Mao K B, Sun Z W, Ma Y and Zhao F. 2014. Method for detecting cloud at night from VIIRS data based on DNB. Remote Sensing for Land and Resources, 26(3): 74-79
  16. 16.
    Yan S M and Wu G. 2015. Increase in haze pollutions in china due to nocturnal emissions. Guangxi Sciences, 22(6): 675-680
  17. 17.
    Yu Y, Hu X Q, Min M, Xu T F, He Y Q, Chen L and Xu R H. 2018. NPP/Visible infrared image radiometer suite low-light image fusion algorithm for city lights in mid-eastern China. Laser and Optoelectronics Progress, 55(10): 102804
  18. 18.
    Zhang J, Reid J S, Miller S D and Turk F J. 2008. Strategy for studying nocturnal aerosol optical depth using artificial lights. International Journal of Remote Sensing, 29(16): 4599-4613
  19. 19.
    Zhao X R, Shi H Q, Yang P L, Zhang L, Fang X and Liang K. 2017. Inversion algorithm of PM2.5 air quality based on nighttime light data from NPP-VIIRS. Journal of Remote Sensing, 21(2): 291-299

Читать полностью

The above content is generated by Large Model Translation. The translated content is for reference only. We do not assume any commercial or legal responsibilty for any consequences arising from the use of our website