Advertisement

Environmental Science and Pollution Research

, Volume 26, Issue 8, pp 7969–7979 | Cite as

Long-term spatiotemporal variations of aerosol optical depth over Yellow and Bohai Sea

  • Xiaojing Shen
  • Muhammad Bilal
  • Zhongfeng QiuEmail author
  • Deyong Sun
  • Shengqiang Wang
  • Weijun Zhu
Research Article

Abstract

In this study, MODerate resolution Imaging Spectroradiometer (MODIS) Collection 6.1 (C6.1) level-2 Dark Target (DT) Aerosol Optical Depth (AOD) observations at 550 nm (AOD550) for the highest quality flag assurance (QA = 3) were obtained to analyze spatiotemporal variations of aerosol optical properties over the Yellow and the Bohai Sea from 2002 to 2017. Spectral AOD observations at 470 nm (AOD470) and 660 nm (AOD660) were obtained to calculate Angstrom Exponent (AE470–660) and classify the aerosol types including clean continental (CC), clean maritime (CM) biomass and urban industrial (BUI), dust (D), and mixed (MXD) aerosol types. Results showed a very distinct spatial pattern of AOD distribution over the Bohai Sea which looks suspicious, i.e., high aerosol loadings (AOD > 0.8) throughout the entire time period, whereas relative low AOD distribution was observed over the adjacent land pixels especially in autumn and winter, which suggested that the DT algorithm might be influenced by a large number of sediments located in the Bohai Sea. Significant differences in spatial distributions were found in different seasons in terms of area coverage as a maximum number of pixels were available during autumn, and regional high and low aerosol loadings were observed during autumn and summer, respectively. Trend analysis from 2002 to 2017 showed that AOD was increased up to 0.04 over the Bohai Sea and decreased up to 0.04 over the Yellow Sea, and this trend varies from month to month. Aerosol classification showed significant contributions of BUI and CC over the region, and contributions of CM, DUST, and MXD aerosols over the Yellow Sea were relatively high compared to the Bohai Sea.

Keywords

AOD MODIS DT Bohai Sea Yellow Sea Aerosol type 

Notes

Acknowledgments

The authors would like to acknowledge the NASA Goddard Space Flight Center for MODIS data. We are thankful to Devin White (Oak Ridge National Laboratory) for the MODIS Conversion Tool Kit (MCTK).

Funding information

This research was jointly supported by the National Key Research and Development Program of China (No. 2016YFC1400901), the National Natural Science Foundation of China (Nos. 41576172 and 41506200), the Provincial Natural Science Foundation of Jiangsu in China (Nos. BK20161532, BK20151526, BK20150914), and the National Program on Global Change and Air-sea Interaction (No. GASI-03-03-01-01).

References

  1. Ackerman S, Strabala K, Menzel P, Frey R, Moeller C, Gumley L (2010) Discriminating clear-sky from cloud with MODIS algorithm theoretical basis document (MOD35)Google Scholar
  2. Adesina AJ, Piketh S, Kanike RK, Venkataraman S (2017) Characteristics of columnar aerosol optical and microphysical properties retrieved from the sun photometer and its impact on radiative forcing over Skukuza (South Africa) during 1999-2010. Environ Sci Pollut Res: 1-12Google Scholar
  3. Alfaro-Contreras R, Zhang J, Reid JS, Christopher S (2017) A study of 15-year aerosol optical thickness and direct shortwave aerosol radiative effect trends using MODIS, MISR, CALIOP and CERES. Atmos Chem Phys 17(22):13849–13868CrossRefGoogle Scholar
  4. Barnes BB, Hu C (2016) Island building in the South China Sea: detection of turbidity plumes and artificial islands using Landsat and MODIS data. Sci Rep 6:33194CrossRefGoogle Scholar
  5. Bennouna Y, Cachorro V, Torres B, Toledano C, Berjón A, De Frutos A, Coppel IAF (2013) Atmospheric turbidity determined by the annual cycle of the aerosol optical depth over North-Center Spain from ground (AERONET) and satellite (MODIS). Atmos Environ 67:352–364CrossRefGoogle Scholar
  6. Bibi H, Alam K, Bibi S (2016) In-depth discrimination of aerosol types using multiple clustering techniques over four locations in indo-Gangetic plains. Atmos Res 181:106–114CrossRefGoogle Scholar
  7. Bilal M, Nichol JE (2015) Evaluation of MODIS aerosol retrieval algorithms over the Beijing-Tianjin-Hebei region during low to very high pollution events. JGR: Atmospheres 120:7941–7957Google Scholar
  8. Bilal M, Nichol J (2017) Evaluation of the NDVI-Based Pixel Selection Criteria of the MODIS C6 Dark Target and Deep Blue Combined Aerosol Product. IEEE J-STARS 10:3448–3453Google Scholar
  9. Bilal M, Nichol JE, Bleiweiss MP, Dubois D (2013) A simplified high resolution MODIS Aerosol Retrieval Algorithm (SARA) for use over mixed surfaces. Remote Sens Environ 136:135–145CrossRefGoogle Scholar
  10. Bilal M, Nichol JE, Chan PW (2014) Validation and accuracy assessment of a Simplified Aerosol Retrieval Algorithm (SARA) over Beijing under low and high aerosol loadings and dust storms. Remote Sens Environ 153:50–60CrossRefGoogle Scholar
  11. Bilal M, Nichol JE, Nazeer M (2016) Validation of Aqua-MODIS C051 and C006 operational aerosol products using AERONET measurements over Pakistan. IEEE J-STARS 9(5):2074–2080Google Scholar
  12. Bilal M, Nichol J, Wang L (2017a) New customized methods for improvement of the MODIS C6 Dark Target and Deep Blue merged aerosol product. Remote Sens Environ 197:115–124CrossRefGoogle Scholar
  13. Bilal M, Nazeer M, Nichol JE (2017b) Validation of MODIS and VIIRS derived aerosol optical depth over complex coastal waters. Atmos Res 186:43–50CrossRefGoogle Scholar
  14. Bilal M, Nazeer M, Qiu Z, Ding X, Wei J (2018a) Global validation of MODIS C6 and C6. 1 merged aerosol products over diverse vegetated surfaces. Remote Sens 10(3):475CrossRefGoogle Scholar
  15. Bilal M, Qiu Z, Campbell JR, Spak SN, Shen X, Nazeer M (2018b) A new MODIS C6 Dark Target and Deep Blue merged aerosol product on a 3 km spatial grid. Remote Sens 10(3):463CrossRefGoogle Scholar
  16. Boiyo R, Kumar KR, Zhao T (2018) Spatial variations and trends in AOD climatology over East Africa during 2002–2016: a comparative study using three satellite data sets. Int J Climatol 38:e1221–e1240CrossRefGoogle Scholar
  17. Carmichael GR, Adhikary B, Kulkarni S, D’Allura A, Tang Y, Streets D, Zhang Q, Bond TC, Ramanathan V, Jamroensan A (2009) Asian aerosols: current and year 2030 distributions and implications to human health and regional climate change. Environ Sci Technol 43:5811–5817CrossRefGoogle Scholar
  18. Charlson RJ, Schwartz SE, Hales JM, Cess RD, Coakley JJ, Hansen JE, Hofmann DJ (1992) Climate forcing by anthropogenic aerosols. Science 255(5043):423–430CrossRefGoogle Scholar
  19. Chu DA, Kaufman Y, Zibordi G, Chern J, Mao J, Li C, Holben B (2003) Global monitoring of air pollution over land from the Earth Observing System-Terra Moderate Resolution Imaging Spectroradiometer (MODIS). JGR: Atmospheres 108Google Scholar
  20. Deng X, He D, Pan D, Sun Z (2010) Analysis of aerosol characteristics over the China Sea by remote sensing. JRS 14:294–312Google Scholar
  21. Gao BC, Kaufman YJ, Tanre D, Li RR (2002) Distinguishing tropospheric aerosols from thin cirrus clouds for improved aerosol retrievals using the ratio of 1.38-μm and 1.24-μm channels. Geophys Res Lett 29Google Scholar
  22. Guo JP, Zhang XY, Wu YR, Zhaxi Y, Che HZ, Ba L, Wang W, Li XW (2011) Spatio-temporal variation trends of satellite-based aerosol optical depth in China during 1980–2008. Atmos Environ 45:6802–6811CrossRefGoogle Scholar
  23. He Q, Li C, Geng F, Lei Y, Li Y (2012) Study on long-term aerosol distribution over the land of East China using MODIS data. Aerosol Air Qual Res 12:304–319CrossRefGoogle Scholar
  24. Herman M, Deuzé J, Devaux C, Goloub P, Bréon F, Tanré D (1997) Remote sensing of aerosols over land surfaces including polarization measurements and application to POLDER measurements. JGR: Atmospheres 102:17039–17049CrossRefGoogle Scholar
  25. Holben BN, Eck T, Slutsker I, Tanre D, Buis J, Setzer A, Vermote E, Reagan J, Kaufman Y, Nakajima T (1998) AERONET—A federated instrument network and data archive for aerosol characterization. Remote Sens Environ 66:1–16CrossRefGoogle Scholar
  26. Holben B, Tanre D, Smirnov A, Eck T, Slutsker I, Abuhassan N, Newcomb W, Schafer J, Chatenet B, Lavenu F (2001) An emerging ground-based aerosol climatology: aerosol optical depth from AERONET. JGR: Atmospheres 106:12067–12097CrossRefGoogle Scholar
  27. Hsu NC, Tsay S-C, King MD, Herman JR (2004) Aerosol properties over bright-reflecting source regions. IEEE Trans Geosci Remote Sens 42:557–569CrossRefGoogle Scholar
  28. Hsu NC, Tsay S-C, King MD, Herman JR (2006) Deep blue retrievals of Asian aerosol properties during ACE-Asia. IEEE Trans Geosci Remote Sens 44:3180–3195CrossRefGoogle Scholar
  29. Hu K, Kumar KR, Kang N, Boiyo R, Wu J (2017) Spatiotemporal characteristics of aerosols and their trends over mainland China with the recent Collection 6 MODIS and OMI satellite datasets. Environ Sci Pollut Res Int 25:1–19Google Scholar
  30. Kahn RA, Gaitley BJ, Martonchik JV, Diner DJ, Crean KA, Holben B (2005) Multiangle Imaging Spectroradiometer (MISR) global aerosol optical depth validation based on 2 years of coincident Aerosol Robotic Network (AERONET) observations. JGR: Atmospheres 110Google Scholar
  31. Kahn RA, Gaitley BJ, Garay MJ, Diner DJ, Eck TF, Smirnov A, Holben BN (2010) Multiangle Imaging SpectroRadiometer global aerosol product assessment by comparison with the Aerosol Robotic Network. JGR: Atmospheres 115Google Scholar
  32. Kaskaoutis DG, Kambezidis HD, Hatzianastassiou N, Kosmopoulos PG (2007) Aerosol climatology: dependence of the Angstrom exponent on wavelength over four AERONET sites. Atmos Chem Phys 7:7347–7397CrossRefGoogle Scholar
  33. Kaskaoutis DG, Badarinath KVS, Shailesh KK, Anu RS, Kambezidis HD (2009) Variations in the aerosol optical properties and types over the tropical urban site of Hyderabad, IndiaGoogle Scholar
  34. Kaufman Y, Tanré D, Remer LA, Vermote E, Chu A, Holben B (1997) Operational remote sensing of tropospheric aerosol over land from EOS moderate resolution imaging spectroradiometer. JGR: Atmospheres 102:17051–17067CrossRefGoogle Scholar
  35. Kaufman YJ, Tanré D, Boucher O (2002) A satellite view of aerosols in the climate system. Nature 419(6903):215–223CrossRefGoogle Scholar
  36. Kinney PL, Gichuru MG, Volavka-Close N, Ngo N, Ndiba PK, Law A, Gachanja A, Gaita SM, Chillrud SN, Sclar E (2011) Traffic impacts on PM2.5 air quality in Nairobi, Kenya. Environ Sci Pol 14:369–378CrossRefGoogle Scholar
  37. Koukouli M, Kazadzis S, Amiridis V, Ichoku C, Balis D, Bais A (2010) Signs of a negative trend in the MODIS aerosol optical depth over the Southern Balkans. Atmos Environ 44:1219–1228CrossRefGoogle Scholar
  38. Kumar KR, Sivakumar V, Reddy RR, Gopal KR, Adesina AJ (2014) Identification and classification of different aerosol types over a subtropical rural site in Mpumalanga, South Africa: seasonal variations as retrieved from the AERONET Sunphotometer. Aerosol Air Qual Res 14:108–123CrossRefGoogle Scholar
  39. Kumar KR, Kang N, Yin Y (2018) Classification of key aerosol types and their frequency distributions based on satellite remote sensing data at an industrially polluted city in the Yangtze River Delta, China. Int J Climatol 38Google Scholar
  40. Leeuw GD, Sogacheva L, Rodriguez E, Kourtidis K, Georgoulias AK, Alexandri G, Amiridis V, Proestakis E, Marinou E, Xue Y (2017) Two decades of satellite observations of AOD over mainland China. Atmos Chem Phys 18:1–33Google Scholar
  41. Leeuw GD, Sogacheva L, Rodriguez E, Kourtidis K, Georgoulias AK, Alexandri G, Amiridis V, Proestakis E, Marinou E, Xue Y (2018) Two decades of satellite observations of AOD over mainland China using ATSR-2, AATSR and MODIS/Terra: data set evaluation and large-scale patterns. Atmos Chem Phys 18:1–33CrossRefGoogle Scholar
  42. Lei Y, Zhang Q, He K, Streets D (2011) Primary anthropogenic aerosol emission trends for China, 1990–2005. Atmos Chem Phys 11:931–954CrossRefGoogle Scholar
  43. Levy RC, Remer LA, Dubovik O (2007a) Global aerosol optical properties and application to moderate resolution imaging Spectroradiometer aerosol retrieval over land. JGR: Atmospheres 112Google Scholar
  44. Levy RC, Remer La, Mattoo S, Vermote EF, Kaufman YJ (2007b) Second-generation operational algorithm: retrieval of aerosol properties over land from inversion of Moderate Resolution Imaging Spectroradiometer spectral reflectance. J Geophys Res 112:D13211CrossRefGoogle Scholar
  45. Levy R, Remer L, Kleidman R, Mattoo S, Ichoku C, Kahn R, Eck T (2010) Global evaluation of the Collection 5 MODIS dark-target aerosol products over land. Atmos Chem Phys 10:10399–10420CrossRefGoogle Scholar
  46. Levy RC, Mattoo S, Munchak LA, Remer LA, Sayer AM, Patadia F, Hsu NC (2013) The Collection 6 MODIS aerosol products over land and ocean. Atmos Meas Tech 6(11):2989–3034CrossRefGoogle Scholar
  47. Li R-R, Kaufman YJ, Gao B-C, Davis CO (2003) Remote sensing of suspended sediments and shallow coastal waters. IEEE Trans Geosci Remote Sens 41:559–566CrossRefGoogle Scholar
  48. Liu J, Saito Y, Wang H, Zhou L, Yang Z (2009) Stratigraphic development during the Late Pleistocene and Holocene offshore of the Yellow River delta, Bohai Sea. J Asian Earth Sci 36:318–331CrossRefGoogle Scholar
  49. Lu Z, Streets DG, Zhang Q, Wang S, Carmichael GR, Cheng YF, Wei C, Chin M, Diehl T, Tan Q (2010) Sulfur dioxide emissions in China and sulfur trends in East Asia since 2000. Atmos Chem Phys 10:6311–6331CrossRefGoogle Scholar
  50. Luo Y, Zheng X, Zhao T, Chen J (2014) A climatology of aerosol optical depth over China from recent 10 years of MODIS remote sensing data. Int J Climatol 34:863–870CrossRefGoogle Scholar
  51. Ma Q, Li Y, Liu J, Chen JM (2017) Long temporal analysis of 3-km MODIS aerosol product over East China. IEEE J-STARS 10(6):2478–2490Google Scholar
  52. Martins JV, Tanré D, Remer L, Kaufman Y, Mattoo S, Levy R (2002) MODIS cloud screening for remote sensing of aerosols over oceans using spatial variability. Geophys Res Lett 29Google Scholar
  53. Ngo NS, Gatari M, Yan B, Chillrud SN, Bouhamam K, Kinneym PL (2015) Occupational exposure to roadway emissions and inside informal settlements in sub-Saharan Africa: a pilot study in Nairobi, Kenya. Atmos Environ 111:179–118CrossRefGoogle Scholar
  54. North PR (2002) Estimation of aerosol opacity and land surface bidirectional reflectance from ATSR-2 dual-angle imagery: operational method and validation. JGR: Atmospheres 107Google Scholar
  55. Pace G, Sarra Ad, Meloni D, Piacentino S (2006) Aerosol optical properties at Lampedusa (Central Mediterranean). 1. Influence of transport and identification of different aerosol types. Atmos Chem Phys 5:4929–4969CrossRefGoogle Scholar
  56. Panicker AS, Lee DI, Kumkar YV, Kim D, Maki M, Uyeda H (2013) Decadal climatological trends of aerosol optical parameters over three different environments in South Korea. Int J Climatol 33:1909–1916CrossRefGoogle Scholar
  57. Prados AI, Kondragunta S, Ciren P, Knapp KR (2007) GOES aerosol/smoke product (GASP) over North America: comparisons to AERONET and MODIS observations. JGR: Atmospheres 112Google Scholar
  58. Proestakis E, Amiridis V, Marinou E, Georgoulias AK, Solomos S, Kazadzis S, Chimot J, Che H, Alexandri G, Binietoglou I (2018) Nine-year spatial and temporal evolution of desert dust aerosols over South and East Asia as revealed by CALIOP. Atmos Chem Phys 18:1–35CrossRefGoogle Scholar
  59. Remer LA, Kaufman Y, Tanré D, Mattoo S, Chu D, Martins JV, Li R-R, Ichoku C, Levy R, Kleidman R (2005a) The MODIS aerosol algorithm, products, and validation. J Atmos Sci 62:947–973CrossRefGoogle Scholar
  60. Remer LA, Kaufman YJ, Tanré D, Mattoo S, Chu DA, Martins JV, Li R-R, Ichoku C, Levy RC, Kleidman RG, Eck TF, Vermote E, Holben BN (2005b) The MODIS aerosol algorithm, products, and validation. J Atmos Sci 62:947–973CrossRefGoogle Scholar
  61. Remer LA, Kleidman RG, Levy RC, Kaufman YJ, Tanré D, Mattoo S, Martins JV, Ichoku C, Koren I, Yu H, Holben BN (2008) Global aerosol climatology from the MODIS satellite sensors. J Geophys Res 113:D14S07CrossRefGoogle Scholar
  62. Remer L, Mattoo S, Levy R, Heidinger A, Pierce R, Chin M (2012) Retrieving aerosol in a cloudy environment: aerosol product availability as a function of spatial resolution. Atmos Meas Tech 5:1823–1840CrossRefGoogle Scholar
  63. Satheesh S, Moorthy KK (2005) Radiative effects of natural aerosols: a review. Atmos Environ 39:2089–2110CrossRefGoogle Scholar
  64. Sayer A, Hsu N, Bettenhausen C, Jeong M, Holben B, Zhang J (2012) Global and regional evaluation of over-land spectral aerosol optical depth retrievals from SeaWiFSGoogle Scholar
  65. Sayer AM, Munchak LA, Hsu NC, Levy RC, Bettenhausen C, Jeong MJ (2015) MODIS Collection 6 aerosol products: comparison between Aqua’s e-Deep Blue, Dark Target, and “merged” data sets, and usage recommendations. Journal of Geophysical Research Atmospheres 119:13,965–913,989CrossRefGoogle Scholar
  66. Sayer AM, Hsu NC, Bettenhausen C, JeongMJ, Meister G (2016) Effect of MODIS Terra radiometric calibration improvements on Collection 6 Deep Blue aerosol products: validation and Terra/Aqua consistency. Journal of Geophysical Research Atmospheres 120: n/a-n/aGoogle Scholar
  67. Seinfeld JH, Pandis SN (2012) Atmospheric chemistry and physics: from air pollution to climate change. John Wiley & SonsGoogle Scholar
  68. Sharobiem WM (2010) Variation and trend in ozone, UVB radiation and aerosol optical depth at Matrouh, Egypt. Int J Remote Sens 31:329–341CrossRefGoogle Scholar
  69. Shen X, Bilal M, Qiu Z, Sun D, Wang S, Zhu W (2018) Validation of MODIS C6 Dark Target aerosol products at 3 km and 10 km spatial resolutions over the China Seas and the Eastern Indian Ocean. Remote Sens 10(4):573CrossRefGoogle Scholar
  70. Smirnov A, Holben BN, Slutsker I, Giles DM, McClain CR, Eck TF, ..., Quinn PK (2009). Maritime aerosol network as a component of aerosol robotic network. JGR: Atmospheres, 114(D6)Google Scholar
  71. Smirnov A, Sayer A, Holben B, Hsu N, Sakerin S, Macke A, Nelson N, Courcoux Y, Smyth T, Croot P (2012) Effect of wind speed on aerosol optical depth over remote oceans, based on data from the Maritime Aerosol Network. Atmos Meas Tech 5:377–388CrossRefGoogle Scholar
  72. Streets DG, Bond T, Carmichael G, Fernandes S, Fu Q, He D, Klimont Z, Nelson S, Tsai N, Wang MQ (2003) An inventory of gaseous and primary aerosol emissions in Asia in the year 2000. JGR: Atmospheres 108Google Scholar
  73. Tan C, Zhao T, Xu X, Liu J, Zhang L, Tang L (2015) Climatic analysis of satellite aerosol data on variations of submicron aerosols over East China. Atmos Environ 123:392–398CrossRefGoogle Scholar
  74. Tanré D, Kaufman Y, Herman M, Mattoo S (1997) Remote sensing of aerosol properties over oceans using the MODIS/EOS spectral radiances. JGR: Atmospheres 102:16971–16988CrossRefGoogle Scholar
  75. Torres O, Bhartia P, Herman J, Sinyuk A, Ginoux P, Holben B (2002) A long-term record of aerosol optical depth from TOMS observations and comparison to AERONET measurements. J Atmos Sci 59:398–413CrossRefGoogle Scholar
  76. Torres O, Tanskanen A, Veihelmann B, Ahn C, Braak R, Bhartia PK, Veefkind P, Levelt P (2007) Aerosols and surface UV products from Ozone Monitoring Instrument observations: an overview. JGR: Atmospheres 112Google Scholar
  77. Tosca MG, Campbell J, Garay M, Lolli S, Seidel FC, Marquis J, Kalashnikova O (2017) Attributing accelerated summertime warming in the Southeast United States to recent reductions in aerosol burden: indications from vertically-resolved observations. Remote Sens 9(7):674CrossRefGoogle Scholar
  78. Vidot J, Santer R, Aznay O (2008) Evaluation of the MERIS aerosol product over land with AERONET. Atmos Chem Phys 8:7603–7617CrossRefGoogle Scholar
  79. Wei GU, Shi PJ, Liu Y, Xie F, Cai XP (2002) The characteristics of temporal and spatial distribution of negative accumulated temperature in Bohai Sea and north Yellow Sea. JNRGoogle Scholar
  80. Woodward A, Smith KR, Campbell-Lendrum D, Chadee DD, Honda Y, Liu Q et al (2014) Climate change and health: on the latest IPCC report. Lancet 383(9924):1185–1189CrossRefGoogle Scholar
  81. Xiao Q, Zhang H, Choi M, Li S, Kondragunta S, Kim J, Holben B, Levy RC, Liu Y (2016) Evaluation of VIIRS, GOCI, and MODIS Collection 6 AOD retrievals against ground sunphotometer observations over East Asia. Atmos Chem Phys 16:1255–1269CrossRefGoogle Scholar
  82. Yu X, Kumar KR, Lü R, Ma J (2016) Changes in column aerosol optical properties during extreme haze-fog episodes in January 2013 over urban Beijing. Environ Pollut 210:217–226CrossRefGoogle Scholar
  83. Zhang XY, Arimoto R, An ZS (1997) Dust emission from Chinese desert sources linked to variations in atmospheric circulation. Journal of Geophysical Research D Atmospheres 102:28–041Google Scholar
  84. Zhao W, Tang J, Gao F, Lin M (2005) Measurement and study of aerosol optical properties over the Huanghai Sea and the East China Sea in the spring. Acta Oceanol Sin 27:46–53Google Scholar
  85. Solomon, S. (2007) IPCC (2007): climate change the physical science basis. In, AGU Fall Meeting Abstracts (p. 01)Google Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Xiaojing Shen
    • 1
  • Muhammad Bilal
    • 2
  • Zhongfeng Qiu
    • 2
    Email author
  • Deyong Sun
    • 2
  • Shengqiang Wang
    • 2
  • Weijun Zhu
    • 2
  1. 1.School of Atmospheric ScienceNanjing University of Information Science and TechnologyNanjingChina
  2. 2.School of Marine SciencesNanjing University of Information Science and TechnologyNanjingChina

Personalised recommendations