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Satellite Aerosol Optical Depth over Vietnam - An Analysis from VIIRS and CALIOP Aerosol Products

  • Vinh T. Tran
  • Ha V. Pham
  • Thanh T. N. Nguyen
  • Thanh X. Pham
  • Quang Hung Bui
  • Anh X. Nguyen
  • Thuy T. Nguyen
Chapter
Part of the Springer Remote Sensing/Photogrammetry book series (SPRINGERREMO)

Abstract

Satellite aerosol products are useful to address a variety of questions relating to the atmosphere, climate change, air pollution, and human health. Thus, their evaluation followed by validation in different regions of the world can help in refining the products. In this study, VIIRS (2012–2015) and CALIPSO (2006–2015) aerosol products are analyzed and compared for seasonal trend and aerosol subtypes at Nghia Do, Nha Trang, and Bac Lieu AERONET stations located in the north, central, and southern regions of Vietnam, respectively. At Nghia Do station, VIIRS AOD captured the northern seasonal trends well with low errors, and high correlation coefficients. CALIPSO aerosol subtypes have shown polluted dust, biomass burning, polluted continental, clean continental, and desert dust coinciding with the northern climate conditions, agricultural burning, and long-range transport. At Nha Trang station, VIIRS AOD performed poorly with no seasonal trends, large errors, and low correlation coefficients. However, aerosol subtype analysis revealed marine aerosol, polluted continental, polluted dust, biomass burning, and desert dust events over the Nha Trang which are mostly explained by location, local climate conditions, and vegetation burning. For Bac Lieu station, VIIRS AOD quality is the lowest compared to AERONET AOD. No seasonal trend has been captured and the errors are extremely high in rainy and dry seasons at this station. CALIPSO aerosol subtypes are marine aerosol, polluted continental, polluted dust, biomass burning, and clean continental which could be explained by location, heat island, and local paddy rice seasonality. In overall, evaluation of VIIRS and CALIPSO aerosol products over Vietnam provides useful insights on their utility and potential applications in aerosol and air quality research.

Keywords

VIIRS CALIPSO AERONET Aerosol optical depth Seasonal trend Aerosol subtypes 

Notes

Acknowledgements

This study was supported by Space Technology Institute, Vietnam Academy of Science under Grant VT/UD-06/14-15. We are grateful to VIIRS, CALIPSO, and AERONET PI(s) for free data sharing. We would like to acknowledge the contribution of the Southern African Systems Analysis Centre, the National Research Foundation and the Department of Science and Technology in South Africa as well as the International Institute for Applied System Analysis.

References

  1. Atmospheric Science Data Center (ASDC) CALIPSO quality statements Lidar Level 2 cloud and aerosol layer products version releases: 3.01, 3.02. https://eosweb.larc.nasa.gov/sites/default/files/project/calipso/quality_summaries/CALIOP_L2LayerProducts_3.01.pdf. Accessed 29 Feb 2016
  2. Badarinath KVS, Kharol SK, Latha KM, Chand TR, Prasad VK, Jyothsna AN, Samatha K (2007) Multiyear ground-based and satellite observations of aerosol properties over a tropical urban area in India. Atmos Sci Lett 8(1):7–13CrossRefGoogle Scholar
  3. Badarinath KVS, Kharol SK, Krishna Prasad V, Kaskaoutis DG, Kambezidis HD (2008) Variation in aerosol properties over Hyderabad, India during intense cyclonic conditions. Int J Remote Sens 29(15):4575–4597CrossRefGoogle Scholar
  4. Badarinath KVS, Sharma AR, Kharol SK, Prasad VK (2009) Variations in CO, O3 and black carbon aerosol mass concentrations associated with planetary boundary layer (PBL) over tropical urban environment in India. J Atmos Chem 62(1):73–86CrossRefGoogle Scholar
  5. Bhoi S, Qu JJ, Dasgupta S (2009) Multi-sensor study of aerosols from 2007 Okefenokee forest fire. J Appl Remote Sens 3(1):031501–031501CrossRefGoogle Scholar
  6. Biswas S, Vadrevu KP, Lwin ZM, Lasko K, Justice CO (2015) Factors controlling vegetation fires in protected and non-protected areas of Myanmar. PLoS One 10(4):e0124346CrossRefGoogle Scholar
  7. Cliff ID, Robert FP, Paul AS (2005) Airborne particulate matter and human health: a review. Aerosol Sci Tech 39:737–749CrossRefGoogle Scholar
  8. Cohen DD, Crawford J, Stelcer E, Bac VT (2010) Long range transport of fine particle windblown soils and coal fired power station emissions into Hanoi between 2001 to 2008. Atmos Environ 44(31):3761–3769CrossRefGoogle Scholar
  9. Dominici F, Peng RD, Bell M, Pham L, Mcdermott D, Zeger J, Samet J (2006) Fine particulate air pollution and hospital admission for cardiovascular and respiratory diseases. J Am Med Assoc 295:1127–1134CrossRefGoogle Scholar
  10. Hayasaka H, Noguchi I, Putra EI, Yulianti N, Vadrevu K (2014) Peat-fire-related air pollution in Central Kalimantan, Indonesia. Environ Pollut 195):257–266CrossRefGoogle Scholar
  11. Hien PD, Bac VT, Thinh NTH (2004) PMF receptor modelling of fine and coarse PM10 in air masses governing monsoon conditions in Hanoi, northern Vietnam. Atmos Environ 38:189–201CrossRefGoogle Scholar
  12. Hobbs PV (1993) Aerosol–cloud–climate interactions. Academic, San DiegoGoogle Scholar
  13. Hsu NC, Tsay SC, King MD, Herman JR (2004) Aerosol properties over bright-reflecting source regions. IEEE Trans Geosci Remote Sens 42:557–569CrossRefGoogle Scholar
  14. Hsu NC, Tsay SC, King MD, Herman JR (2006) Deep blue retrievals of Asian aerosol properties during ACE-Asia. IEEE Trans Geosci Remote Sens 44:3180–3195CrossRefGoogle Scholar
  15. Huang J, Minnis P, Chen B, Huang Z, Liu Z, Zhao Q, Yi Y, Ayers JK (2008) Long-range transport and vertical structure of Asian dust from CALIPSO and surface measurements during PACDEX. J Geophys Res 113:D23212.  https://doi.org/10.1029/2008JD010620 CrossRefGoogle Scholar
  16. Huang K, Fu JS, Hsu NC, Gao Y, Dong X, Tsay SC, Lam YF (2012) Impact assessment of biomass burning on air quality in Southeast and East Asia during BASE-ASIA. Atmos Environ 78(2013):291–302Google Scholar
  17. Ichoku C, Chu DA, Mattoo S, Kaufman DA, Remer LA, Tanré D, Slusker I, Holben BN (2002) A spatio-temporal approach for global validation and analysis of MODIS aerosol products. Geophys Res Lett 29.  https://doi.org/10.1029/2001GL013206
  18. Jeong MJ, Hsu NC (2008) Retrievals of aerosol single-scattering albedo and effective aerosol layer height for biomass-burning smoke: synergy derived from “A-Train” sensors. Geophys Res Lett 35:L24801.  https://doi.org/10.1029/2008GL036279 CrossRefGoogle Scholar
  19. Junge CE (1952) Die Konstitution der Atmospherischen Aerosols. Annalender Meteorologie 1:128–135Google Scholar
  20. Kahn R, Banerjee P, McDonald D (2001) Sensitivity of multiangle imaging to natural mixtures of aerosols over ocean. J Geophys Res 106(D16):18219–18238CrossRefGoogle Scholar
  21. Kant Y, Ghosh AB, Sharma MC, Gupta PK, Prasad VK, Badarinath KVS, Mitra AP (2000a) Studies on aerosol optical depth in biomass burning areas using satellite and ground-based observations. Infrared Phys Technol 41(1):21–28CrossRefGoogle Scholar
  22. Kant Y, Prasad VK, Badarinath KVS (2000b) Algorithm for detection of active fire zones using NOAA AVHRR data. Infrared Phys Technol 41(1):29–34CrossRefGoogle Scholar
  23. Kaufman YJ, Sendra C (1988) Algorithm for automatic atmospheric corrections to visible and near-IR satellite imagery. Int J Remote Sens 9:1357–1381CrossRefGoogle Scholar
  24. Kaufman YJ, Gobron N, Pinty B, Widlowski JL, Verstraete MM (2002a) Relationship between surface reflectance in the visible and mid-IR used in MODIS Aerosol Algorithm–theory. Geophys Res Lett 29:2116.  https://doi.org/10.1029/2001GL014492 CrossRefGoogle Scholar
  25. Kaufman YJ, Tanre D, Boucher O (2002b) A satellite view of aerosols in the climate system. Nature 419:215–223CrossRefGoogle Scholar
  26. King MD, Kaufman YJ, Tanré D, Nakajima T (1999) Remote sensing of tropospheric aerosols from space: past, present, and future. Bull Am Meteorol Soc 80:2229–2259CrossRefGoogle Scholar
  27. Kittaka C, Winker DM, Vaughan MA, Omar A, Remer LA (2011) Intercomparison of column aerosol optical depths from CALIPSO and MODIS-Aqua. Atmos Meas Tech 4:131–141.  https://doi.org/10.5194/amt-4-131-2011 CrossRefGoogle Scholar
  28. Kokhanovsky A, Breon F, Cacciari A, Carboni E, Diner D, Dinicolantonio W, Grainger R, Grey W, Holler R, Lee K (2007) Aerosol remote sensing over land: a comparison of satellite retrievals using different algorithms and instruments. Atmos Res 85:372–394CrossRefGoogle Scholar
  29. Labonne M, Bréon FM, Chevallier F (2007) Injection height of biomass burning aerosols as seen from a spaceborne lidar. Geophys Res Lett 34:L11806.  https://doi.org/10.1029/2007GL029311 CrossRefGoogle Scholar
  30. Lau KM, Ramanathan V, Wu GX, Li Z, Tsay SC, Hsu C, Sikka R, Holben B, Lu D, Tartari G, Chin M, Kuodelova P, Chen H, Ma Y, Huang J, Taniguchi J, Zhang R (2008) The joint Aerosol-monsoon experiment: a new challenge for monsoon climate research. Bull Am Meteorol Soc 89:369–383CrossRefGoogle Scholar
  31. Le TH, Nguyen TNT, Lasko K, Ilavajhala S, Vadrevu KPJC (2014) Vegetation fires and air pollution in Vietnam. Environ Pollut 195:267–275CrossRefGoogle Scholar
  32. Lee KH, Kim YJ (2010) Satellite remote sensing of asian aerosols: a case study of clean, polluted and dust storm days. Atmos Meas Tech 3:2651–2680CrossRefGoogle Scholar
  33. Lin NH, Tsay S-C, Maring HB et al (2013) An overview of regional experiments on case study. Environ Res Lett 10(9):95016–95028Google Scholar
  34. Liu Z, Vaughan M, Winker D, Kittaka C, Getzewich B, Kuehn R, Omar A, Powell K, Trepte C, Hostetler C (2009) The CALIPSO lidar cloud and aerosol discrimination: version 2 algorithm and initial assessment of performance. J Atmos Oceanic Technol 26(7):1198–1213CrossRefGoogle Scholar
  35. Liu H, Laszlo I, Kondragunta S, Remer LA, Huang J (2012) Evaluation of global VIIRS aerosol EDR product with MODIS and AERONET. American Geophysical Union, Fall Meeting 2012, abstract #A13J-0317Google Scholar
  36. Martonchik JV, Diner DJ, Kahn RA, Ackerman TP, Verstraete MM, Pinty B, Gordon HRJ (1998) Techniques for the retrieval of aerosol properties over land and ocean using multiangle imaging. IEEE Trans Geosci Remote Sens 36:1212–1227CrossRefGoogle Scholar
  37. Mie G (1908) On optical characteristics of turbid media, with special reference to colloid metallic solutions. Ann Phys Rehabil Med 25:377–445Google Scholar
  38. Mielonen T, Levy RC, Aaltonen V, Komppula M, Leeuw G, Huttunen J, Lihavainen H, Kolmonen P, Lehtinen KEJ, Arola A (2011) Evaluating the assumptions of surface reflectance and aerosol type selection within the MODIS aerosol retrieval over land: the problem of dust type selection. Atmos Meas Tech 4(201–214):2011Google Scholar
  39. Nguyen DN, Nguyen TH (2004) The climate and climate resources of Vietnam. Agriculture Publisher, HanoiGoogle Scholar
  40. Nguyen TNT, Ta VC, Le TH, Mantovani S (2013) Particulate matter concentration estimation from satellite aerosol and meteorological parameters, data-driven approaches. In Proceedings of fifth international conference (KSE 20130) Knowledge and Systems Engineering, 1(II), pp 351–362Google Scholar
  41. Nguyen TNT, Bui QH, Pham VH, Luu VH, Man DC, Pham NH, Le TH, Nguyen TT (2015) Particulate matter concentration mapping from MODIS satellite data: a Vietnamese case study. Environ Res Lett 10(9):95016–95028CrossRefGoogle Scholar
  42. Nunes TV, Pio CA (1993) Carbonaceous aerosols in industrial and coastal atmospheres. Atmos Environ Part A 27(8):1339–1346CrossRefGoogle Scholar
  43. Omar AH, Winker DM, Vaughan MA, Hu Y, Trepte CR, Ferrare RA, Lee KP, Hostetler CA, Kittaka C, Rogers RR, Kuehn RE, Liu Z (2009) The CALIPSO automated aerosol classification and lidar ratio selection algorithm. J Atmos Oceanic Tech 26:1994–2014.  https://doi.org/10.1175/2009JTECHA1231.1 CrossRefGoogle Scholar
  44. Pham NT, Pham TD (1993) The climate of Vietnam. Science and Technology, Hanoi. (inVietnamese)Google Scholar
  45. Pham XT, Nguyen XA, Pham LK, Do NT, Hoang HS, Au DT (2015) Characteristics of aerosol optical depth retrieved from AERONET in Vietnam and comparison with MODIS data. J Sci Earth 37(3):252–263. (in Vietnamese)Google Scholar
  46. Prasad VK, Kant Y, Gupta PK, Elvidge C, Badarinath KVS (2002) Biomass burning and related trace gas emissions from tropical dry deciduous forests of India: A study using DMSP-OLS data and ground-based measurements. Int J Remote Sens 23(14):2837–2851CrossRefGoogle Scholar
  47. Prasad VK, Lata M, Badarinath KVS (2003) Trace gas emissions from biomass burning from northeast region in India—estimates from satellite remote sensing data and GIS. Environmentalist 23(3):229–236CrossRefGoogle Scholar
  48. Qi YL, Ge JM, Huang JP (2013) Spatial and temporal distribution of MODIS and MISR aerosol optical depth over northern China and comparison with AERONET. Chin Sci Bull 58(20):249–2506.  https://doi.org/10.1007/s11434-013-5678-5 CrossRefGoogle Scholar
  49. Uno I, Yumimoto K, Shimizu A, Hara Y, Sugimoto N, Wang Z, Liu Z, Winker DM (2008) 3D structure of Asian dust transport revealed by CALIPSO lidar and a 4DVAR dust model. Geophys Res Lett 35:L06803.  https://doi.org/10.1029/2007GL032329 CrossRefGoogle Scholar
  50. Vadrevu KP (2008) Analysis of fire events and controlling factors in eastern India using spatial scan and multivariate statistics. Geogr Ann Ser B 90(4):315–328CrossRefGoogle Scholar
  51. Vadrevu KP, Justice CO (2011) Vegetation fires in the Asian region: satellite observational needs and priorities. Glob Environ Res 15(1):65–76Google Scholar
  52. Vadrevu KP, Eaturu A, Badarinath KV (2006) Spatial distribution of forest fires and controlling factors in Andhra Pradesh, India using spot satellite datasets. Environ Monit Assess 123(1):75–96CrossRefGoogle Scholar
  53. Vadrevu KP, Badarinath KVS, Anuradha E (2008) Spatial patterns in vegetation fires in the Indian region. Environ Monit Assess 147(1-3):1–13CrossRefGoogle Scholar
  54. Vadrevu KP, Csiszar I, Ellicott E, Giglio L, Badarinath KVS, Vermote E, Justice C (2013a) Hotspot analysis of vegetation fires and intensity in the Indian region. IEEE J Sel Top Appl Earth Obs Remote Sens 6(1):224–238CrossRefGoogle Scholar
  55. Vadrevu KP, Giglio L, Justice C (2013b) Satellite based analysis of fire–carbon monoxide relationships from forest and agricultural residue burning (2003–2011). Atmos Environ 64):179–191CrossRefGoogle Scholar
  56. Vadrevu KP, Lasko K, Giglio L, Justice C (2014) Analysis of Southeast Asian pollution episode during June 2013 using satellite remote sensing datasets. Environ Pollut 195:245–256CrossRefGoogle Scholar
  57. Vadrevu KP, Lasko K, Giglio L, Justice C (2015) Vegetation fires, absorbing aerosols and smoke plume characteristics in diverse biomass burning regions of Asia. Environ Res Lett 10(10):105003CrossRefGoogle Scholar
  58. Vaughan M, Powell K, Kuehn R, Young S, Winker D, Hostetler C, Hunt W, Liu Z, McGill M, Getzewich B (2009) Fully automated detection of cloud and aerosol layers in the CALIPSO lidar measurements. J Atmos Oceanic Tech 26:2034–2050CrossRefGoogle Scholar
  59. Vay SA, Choi Y, Vadrevu KP, Blake DR, Tyler SC, Wisthaler A, Hecobian A, Kondo Y, Diskin GS, Sachse GW, Woo JH (2011) Patterns of CO2 and radiocarbon across biomass burning aerosols and related pollutants in Southeast Asia: from BASE-ASIA and the Dongsha experiment to 7-SEAS. Atmos Environ 78(2013):1–19Google Scholar
  60. Wang X, Huang J, Ji M, Higuchi K (2008) Variability of East Asia dust events and their long-term trend. Atmos Environ 42:3156–3165CrossRefGoogle Scholar
  61. Winker DM, Pelon JR, Mccormick MP (2003) The CALIPSO Mission: space borne lidar for observation of aerosols and clouds, in lidar remote sensing for industry and environment monitoring III, In: Singh UN, Itabe T, Liu Z (eds) Proceedings of the meeting, SPIE, vol 4893, pp 1–11. SPIE EurOpto Series, BellinghamGoogle Scholar
  62. Winker D, Vaughan M, Omar A, Hu Y, Powell K, Liu Z, Hunt W, Young S (2009) Overview of the CALIPSO mission and CALIOP data processing algorithm. J Atmos Oceanic Tech 26:2310–2323CrossRefGoogle Scholar
  63. Winker DM, Pelon J, Coakley JA, Ackerman et al (2010) The CALIPSO mission: a global 3D view of aerosols and clouds. Bull Am Meteorol Soc 91:1211–1229CrossRefGoogle Scholar
  64. Wong MS, Nichol JE, Lee KH (2011) An operational MODIS aerosol retrieval algorithm at high spatial resolution, and its application over a complex urban region. Atmos Res 99:570–589CrossRefGoogle Scholar
  65. Xiao Q, Liu Y, Kondragunta S, Zhang H (2014) Evaluation of VIIRS, GOCI, and MODIS Collection 6 AOD retrievals against ground sunphotometer measurements over East Asia. Atmos Chem Phys 16(1255–1269):2016.  https://doi.org/10.5194/acp-16-1255-2016 CrossRefGoogle Scholar

Copyright information

© This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2018

Authors and Affiliations

  • Vinh T. Tran
    • 1
    • 2
  • Ha V. Pham
    • 2
  • Thanh T. N. Nguyen
    • 2
  • Thanh X. Pham
    • 3
  • Quang Hung Bui
    • 4
  • Anh X. Nguyen
    • 3
  • Thuy T. Nguyen
    • 2
  1. 1.Hanoi Pedagogical University 2Vinh PhucVietnam
  2. 2.Vietnam National University Hanoi, University of Engineering and TechnologyHanoiVietnam
  3. 3.Institute of Geophysics, Vietnam Academy of Science and TechnologyHanoiVietnam
  4. 4.University of Engineering and Technology, Vietnam National University HanoiHanoiVietnam

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