Skip to main content
SpringerLink
Log in

Spatio-Temporal Variability of Global Aerosol Optical Depth During 2000–2019

  • Conference paper
  • First Online:
Spatial Data and Intelligence (SpatialDI 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13614))

Included in the following conference series:

  • 302 Accesses

Abstract

In the past two decades, the deterioration of air quality around the world has attracted increasing attention. Research of air pollution based on aerosol optical depth (AOD) is particularly significant. In this article, temporal and spatial changes of global aerosol optical depth from 2000 to 2019 are studied based on MODIS AOD product data, in order to reveal the change pattern of global air pollution in the past two decades. As a result of the study, the overall global AOD has been on an upward trend over the period 2000–2019. Changes in AOD during the year have obvious seasonality, in order of which is spring > summer > autumn > winter. Central Africa, South Asia and East Asia have the highest AOD, and therefore the air pollution in these areas is the most serious, however AOD in these areas is generally on the decline.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 54.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 69.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Carmichael, G.R., Adhikary, B., Kulkarni, S., D’Allura, A., Tang, Y.H., Streets, D., et al.: Asian aerosols: current and year 2030 distributions and implications to human health and regional climate change. Environ. Sci. Technol. 43(15), 5811–5817 (2009)

    Article  Google Scholar 

  2. Deng, X.L., He, D.Y., Pan, D.L., Sun, Z.B.: Analysis of aerosol characteristics over the China Sea by remote sensing. J. Remote. Sens. 14(2), 294–312 (2010)

    Google Scholar 

  3. Satheesh, S., Krishnamoorthy, K.: Radiative effects of natural aerosols: a review. Atmos. Environ. 39(11), 2089–2110 (2005)

    Article  Google Scholar 

  4. Bian, H., Chin, M., Rodriguez, J.M., Yu, H., Penner, J.E., Strahan, S.: Sensitivity of aerosol optical thickness and aerosol direct radiative effect to relative humidity. Atmos. Chem. Phys. 9(7), 2375–2386 (2009)

    Article  Google Scholar 

  5. Sellers, W.D.: A global climatic model based on the energy balance of the Earth-Atmosphere system. J. Appl. Meteorol. Clim. 8(3), 392–400 (1969)

    Article  Google Scholar 

  6. Seinfeld, J.H., Pandis, S.N., Noone, K.: Atmospheric chemistry and physics: from air pollution to climate change. Phys. Today 51(10), 88–90 (1998)

    Article  Google Scholar 

  7. Xia, X.A., Chen, H.B., Goloub, P., Zong, X.M., Zhang, W.X., Wang, P.C.: Climatological aspects of aerosol optical properties in North China Plain based on ground and satellite remote-sensing data. J. Quant. Spectrosc. Ra. 127, 12–23 (2013)

    Article  Google Scholar 

  8. Hu, J.L., Wang, Y.G., Ying, Q., Zhang, H.L.: Spatial and temporal variability of PM2.5 and PM10 over the North China Plain and the Yangtze River Delta. China. Atmos. Environ. 95, 598–609 (2014)

    Article  Google Scholar 

  9. Watts, N., Adger, W.N., Agnolucci, P., Blackstock, J., Byass, P., Cai, W.J., et al.: Health and climate change: Policy responses to protect public health. Lancet 386(10006), 1861–1914 (2015)

    Article  Google Scholar 

  10. Thurston, G.D., Ahn, J., Cromar, K.R., Shao, Y., Reynolds, H.R., Jerrett, M., et al.: Ambient particulate matter air pollution exposure and mortality in the NIH-AARP diet and health cohort. Environ. Health Persp. 124(4), 484–490 (2016)

    Article  Google Scholar 

  11. Huang, J.P., Ji, M.X., Xie, Y.K., Wang, S.S., He, Y.L., Ran, J.J.: Global semi-arid climate change over last 60 years. Clim. Dynam. 46(3–4), 1131–1150 (2016)

    Article  Google Scholar 

  12. He, Q.Q., Zhang, M., Huang, B.: Spatio-temporal variation and impact factors analysis of satellite-based aerosol optical depth over China from 2002 to 2015. Atmos. Environ. 129, 79–90 (2016)

    Article  Google Scholar 

  13. Luo, Y.X., Zheng, X.B., Zhao, T.L., Chen, J.: A climatology of aerosol optical depth over China from recent 10 years of MODIS remote sensing data. Int. J. Climatol. 34(3), 863–870 (2014)

    Article  Google Scholar 

  14. van Donkelaar, A., Martin, R.V., Brauer, M., Kahn, R., Levy, R., Verduzco, C., et al.: Global estimates of ambient fine particulate matter concentrations from satellite-based aerosol optical depth: development and application. Environ. Health Persp. 118(6), 847–855 (2010)

    Article  Google Scholar 

  15. Cao, C.X., Zheng, S., Singh, R.P.: Characteristics of aerosol optical properties and meteorological parameters during three major dust events (2005–2010) over Beijing. China. Atmos. Res. 150, 129–142 (2014)

    Article  Google Scholar 

  16. Cheng, L., Li, L., Chen, L., Hu, S., Yuan, L., Liu, Y., et al.: Spatiotemporal variability and influencing factors of aerosol optical depth over the Pan Yangtze River Delta during the 2014–2017 period. Int. J. Env. Res. Pub. He. 16(19), 3522 (2019)

    Article  Google Scholar 

  17. Chi, Y.F., Zuo, S.D., Ren, Y., Chen, K.C.: The spatiotemporal pattern of the aerosol optical depth (AOD) on the canopies of various forest types in the exurban national park: a case in Ningbo city, eastern China. Adv. Meteorol. 2019, 1–12 (2019)

    Article  Google Scholar 

  18. Kuang, Q., Wang, Y.: Spatial-temporal characteristics of the aerosol optical depth (AOD) derived from longterm (1980–2018) MERRA-2 over Guangdong. ISPRS Archives XLII-3/W9, 103–108 (2019)

    Google Scholar 

  19. Shen, X., Bilal, M., Qiu, Z., Sun, D., Wang, S., Zhu, W.: Long-term spatiotemporal variations of aerosol optical depth over Yellow and Bohai Sea. Environ. Sci. Pollut. Res. 26(8), 7969–7979 (2019). https://doi.org/10.1007/s11356-019-04203-4

    Article  Google Scholar 

  20. Xue, R., Ai, B., Lin, Y.Y., Pang, B.B., Shang, H.S.: Spatial and temporal distribution of aerosol optical depth and its relationship with urbanization in Shandong Province. Atmosphere-Basel 10(3), 110 (2019)

    Article  Google Scholar 

  21. Yang, Q.Q., Yuan, Q.Q., Yue, L.W., Li, T.W., Shen, H.F., Zhang, L.P.: The relationships between PM2.5 and aerosol optical depth (AOD) in mainland China: about and behind the spatio-temporal variations. Environ. Pollut. 248, 526–535 (2019)

    Article  Google Scholar 

  22. Feng, Y., Chen, D.M., Zhang, X.H.: Atmospheric aerosol pollution across China: a spatiotemporal analysis of satellite-based aerosol optical depth during 2000–2016. Int. J. Digit. Earth 12(7), 843–857 (2018)

    Article  Google Scholar 

  23. Filonchyk, M., Yan, H., Zhang, Z.: Analysis of spatial and temporal variability of aerosol optical depth over China using MODIS combined Dark Target and Deep Blue product. Theoret. Appl. Climatol. 137(3–4), 2271–2288 (2018). https://doi.org/10.1007/s00704-018-2737-5

    Article  Google Scholar 

  24. He, Q.Q., Gu, Y.F., Zhang, M.: Spatiotemporal patterns of aerosol optical depth throughout China from 2003 to 2016. Sci. Total Environ. 653, 23–35 (2019)

    Article  Google Scholar 

  25. Islam, M.N., Ali, M.A., Islam, M.M.: Spatiotemporal investigations of aerosol optical properties over Bangladesh for the period 2002–2016. Earth Syst. Environ. 3(3), 563–573 (2019)

    Article  Google Scholar 

  26. Xie, G.Q., Wang, M., Pan, J., Zhu, Y.: Spatio-temporal variations and trends of MODIS C6.1 dark target and deep blue merged aerosol optical depth over China during 2000–2017. Atmos. Environ. 214, 116846 (2019)

    Article  Google Scholar 

  27. Kumar, A.: Spatio-temporal variations in satellite based aerosol optical depths & aerosol index over Indian subcontinent: Impact of urbanization and climate change. Urban Clim. 32, 100598 (2020)

    Article  Google Scholar 

  28. Li, Z.Q., Zhao, S.H., Edwards, R., Wang, W.B., Zhou, P.: Characteristics of individual aerosol particles over Ürümqi Glacier No. 1 in eastern Tianshan, central Asia, China. Atmos. Res. 99(1), 57–66 (2011)

    Article  Google Scholar 

  29. Che, H.Z., Wang, Y.Q., Sun, J.Y., Zhang, X.C., Zhang, X.Y., Guo, J.P.: Variation of aerosol optical properties over the Taklimakan Desert in China. Aerosol. Air Qual. Res. 13(2), 777–785 (2013)

    Article  Google Scholar 

  30. Ge, J.M., Huang, J.P., Xu, C.P., Qi, Y.L., Liu, H.Y.: Characteristics of Taklimakan dust emission and distribution: a satellite and reanalysis field perspective. J. Geophys. Res. Atmos. 119(20), 11772–11783 (2014)

    Article  Google Scholar 

  31. Zong, X.M., Xia, X.A., Che, H.Z.: Validation of aerosol optical depth and climatology of aerosol vertical distribution in the Taklimakan Desert. Atmos. Pollut. Res. 6(2), 239–244 (2015)

    Article  Google Scholar 

  32. Che, H.Z., Xia, X.A., Zhu, J., Wang, H., Wang, Y.Q., Sun, J.Y., et al.: Aerosol optical properties under the condition of heavy haze over an urban site of Beijing, China. Environ. Sci. Pollut. R. 22(2), 1043–1053 (2015)

    Article  Google Scholar 

  33. Wang, Y.F., Zhang, W.Y., Kong, L.B., Wang, J.J.: Analysis of applicability and characteristics of MODIS aerosol products in agricultural regions (in Chinese). Remote Sens. Technol. Appl. 28(03), 505–510 (2013)

    Google Scholar 

  34. Song, W.Z., Jia, H.F., Huang, J.F., Zhang, Y.Y.: A satellite-based geographically weighted regression model for regional PM2.5 estimation over the Pearl River Delta region in China. Remote Sens. Environ. 154, 1–7 (2014)

    Article  Google Scholar 

  35. Levy, R.C., Remer, L.A., Mattoo, S., Vermote, E.F., Kaufman, Y.J.: Second-generation operational algorithm: retrieval of aerosol properties over land from inversion of Moderate Resolution Imaging Spectroradiometer spectral reflectance. J. Geophys. Res. Atmos. 112(D13), D13211 (2007)

    Google Scholar 

  36. Levy, R.C., Mattoo, S., Munchak, L.A., Remer, L.A., Sayer, A.M., Patadia, F., et al.: The collection 6 MODIS aerosol products over land and ocean. Atmos. Meas. Tech. 6(11), 2989–3034 (2013)

    Article  Google Scholar 

  37. Hsu, N.C., Jeong, M.J., Bettenhausen, C., Sayer, A.M., Hansell, R., Seftor, C.S., et al.: enhanced deep blue aerosol retrieval algorithm: the second generation. J. Geophys. Res. Atmos. 118(16), 9296–9315 (2013)

    Article  Google Scholar 

  38. Wei, J., Peng, Y.R., Guo, J.P., Sun, L.: Performance of MODIS Collection 6.1 Level 3 aerosol products in spatial-temporal variations over land. Atmos. Environ. 206, 30–44 (2019)

    Article  Google Scholar 

  39. Christopher, S., Gupta, P.: Global distribution of column satellite aerosol optical depth to surface PM2.5 relationships. Remote Sens.-Basel 12(12), 1985 (2020)

    Article  Google Scholar 

  40. Guo, J.P., Zhang, X.Y., Wu, Y.R., Zhaxi, Y.Z., Che, H.Z., La, B., et al.: Spatio-temporal variation trends of satellite-based aerosol optical depth in China during 1980–2008. Atmos. Environ. 45(37), 6802–6811 (2011)

    Article  Google Scholar 

  41. Srivastava, R.: Trends in aerosol optical properties over South Asia. Int. J. Climatol. 37(1), 371–380 (2017)

    Article  Google Scholar 

  42. Jia, Y.T., Rahn, K.A., He, K.B., Wen, T.X., Wang, Y.S.: A novel technique for quantifying the regional component of urban aerosol solely from its sawtooth cycles. J. Geophys. Res. 113(D21), D21309 (2008)

    Article  Google Scholar 

  43. Dickerson, R.R., Kondragunta, S., Stenchikov, G., Civerolo, K.L., Doddridge, B.G., Holben, B.N.: The impact of aerosols on solar ultraviolet radiation and photochemical smog. Science 278(5339), 827–830 (1997)

    Article  Google Scholar 

  44. WMO: Provisional WMO statement on the status of the global climate in 2016. World Meteorological Organization (2016)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Geography and Information Engineering, China University of Geosciences, Wuhan, 430074, China

    Shanshan Lu, Fujiang Liu, Peng Li, Jiayu Tang & Weihua Lin

  2. Shanghai Investigation, Design and Research Institute Co., Ltd., Shanghai, 200335, China

    Fushou Liu

  3. School of Computer Science, China University of Geosciences, Wuhan, 430074, China

    Yan Guo

Authors
  1. Shanshan Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Fujiang Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Fushou Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Peng Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jiayu Tang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Weihua Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Yan Guo
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Fujiang Liu .

Editor information

Editors and Affiliations

  1. Peking University, Wuhan, China

    Huayi Wu

  2. Peking University, Beijing, China

    Yu Liu

  3. Harbin Institute of Technology, Harbin, China

    Jianzhong Li

  4. Department of Computer Science and Information, Renmin University of China, Beijing, China

    Xiaofeng Meng

  5. China University of Geosciences (Wuhan), Wuhan, China

    Qingfeng Guan

  6. Southern University of Science and Technology, Shenzhen, China

    Xuan Song

  7. Jiangxi University of Finance and Economics, Nanchang, China

    Guoqiong Liao

  8. Department of Computer Science and Technology, Tsinghua University, Beijing, China

    Guoliang Li

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Lu, S. et al. (2022). Spatio-Temporal Variability of Global Aerosol Optical Depth During 2000–2019. In: Wu, H., et al. Spatial Data and Intelligence. SpatialDI 2022. Lecture Notes in Computer Science, vol 13614. Springer, Cham. https://doi.org/10.1007/978-3-031-24521-3_12

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-24521-3_12

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-24520-6

  • Online ISBN: 978-3-031-24521-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation