Air Quality, Atmosphere & Health

, Volume 12, Issue 4, pp 503–517 | Cite as

Spatiotemporal distribution of aerosols over the Indian subcontinent and its dependence on prevailing meteorological conditions

  • Sinan NizarEmail author
  • B. M. Dodamani


The prevailing meteorological conditions that influence the advection and diffusion of the atmosphere govern the distribution of atmospheric particles from its sources. The present study explores the spatiotemporal distribution of atmospheric aerosols over the Indian subcontinent (5°–40° N, 65°–100° E) and its dependence on the prevailing meteorological conditions. Eleven years (2002–2012) of Aerosol Optical Depth (AOD) obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) along with meteorological parameters extracted from reanalysis data are analysed at monthly timescales. Wind speed, wind divergence and planetary boundary layer height (PBLH) are studied as parameters for advection and diffusion of atmospheric aerosols. The result shows higher aerosol loading during the monsoon season with increased spatial variability. Wind speed and divergence correlate with AOD values both over land (R = 0.75) and ocean (R = 0.82) with increased aerosol loading at higher wind speeds, which are converging in nature. Owing to the varied climatology of the Indian subcontinent, land and ocean areas were classified into subregions. Analysis was carried out over these subregions to infer the influence of meteorological conditions on aerosol loading. Results are indicative of a distinct characteristic in the prevailing meteorological conditions that influence the distribution of certain aerosol types. Further, the PBLH was analysed as an indicator of atmospheric diffusion to infer its importance in aerosol distribution. The results indicate that PBLH explains almost 30 to 90% of the total variance in AOD over the subregions which is particularly evident during the winter and pre-monsoon seasons.


Aerosol Meteorology Wind speed Wind divergence Planetary boundary layer height India 



The authors would like to thank the Department of Applied Mechanics and Hydraulics, NITK Surathkal, for providing necessary support during the study. The authors gratefully acknowledge the NOAA Air Resources Laboratory for the provision of the HYSPLIT transport and dispersion model and/or READY website ( used in this publication.

Supplementary material

11869_2019_677_MOESM1_ESM.pdf (42 kb)
ESM 1 (PDF 42 kb)


  1. Ainsworth EA, Long SP (2004) What have we learned from 15 years of free-air CO2 enrichment (FACE)? A meta-analytic review of the responses of photosynthesis, canopy properties and plant production to rising CO2. New Phytol 165:351–372. CrossRefGoogle Scholar
  2. Aloysius M, Mohan M, Parameswaran K, George SK, Nair PR (2008) Aerosol transport over the Gangetic basin during ISRO-GBP land campaign-II. Ann Geophys 26:431–440. CrossRefGoogle Scholar
  3. Badarinath KVS, Kharol SK, Kaskaoutis DG, Sharma AR, Ramaswamy V, Kambezidis HD (2010) Long-range transport of dust aerosols over the Arabian Sea and Indian region - a case study using satellite data and ground-based measurements. Glob Planet Chang 72:164–181. CrossRefGoogle Scholar
  4. Cheng S, Chen D, Li J, Wang H, Guo X (2007) The assessment of emission-source contributions to air quality by using a coupled MM5-ARPS-CMAQ modeling system: a case study in the Beijing metropolitan region, China. Environ Model Softw 22:1601–1616. CrossRefGoogle Scholar
  5. Chitranshi S, Sharma SP, Dey S (2015) Satellite-based estimates of outdoor particulate pollution (PM10) for Agra City in northern India. Air Qual Atmos Health 8:55–65. CrossRefGoogle Scholar
  6. Choudhry P, Misra A, Tripathi SN (2012) Study of MODIS derived AOD at three different locations in the Indo Gangetic Plain: Kanpur, Gandhi College and Nainital. Ann Geophys 30:1479–1493. CrossRefGoogle Scholar
  7. Chylek P, Coakley JA (1974) Aerosols and climate. Science 183:75–77. CrossRefGoogle Scholar
  8. Dey S (2004) Influence of dust storms on the aerosol optical properties over the Indo-Gangetic basin. J Geophys Res 109:D20211. CrossRefGoogle Scholar
  9. Ding A, Wang T, Zhao M, Wang T, Li Z (2004) Simulation of sea-land breezes and a discussion of their implications on the transport of air pollution during a multi-day ozone episode in the Pearl River Delta of China. Atmos Environ 38:6737–6750. CrossRefGoogle Scholar
  10. Fuzzi S, Baltensperger U, Carslaw K, Decesari S, Denier van der Gon H, Facchini MC, Fowler D, Koren I, Langford B, Lohmann U, Nemitz E, Pandis S, Riipinen I, Rudich Y, Schaap M, Slowik JG, Spracklen DV, Vignati E, Wild M, Williams M, Gilardoni S (2015) Particulate matter, air quality and climate: lessons learned and future needs. Atmos Chem Phys 15:8217–8299. CrossRefGoogle Scholar
  11. Gautam R, Hsu NC, Lau K-M, Kafatos M (2009a) Aerosol and rainfall variability over the Indian monsoon region: distributions, trends and coupling. Ann Geophys 27:3691–3703. CrossRefGoogle Scholar
  12. Gautam R, Hsu NC, Lau K-M et al (2009b) Enhanced pre-monsoon warming over the Himalayan-Gangetic region from 1979 to 2007. Geophys Res Lett 36:n/a-n/a.
  13. Gelaro R, McCarty W, Suárez MJ, Todling R, Molod A, Takacs L, Randles CA, Darmenov A, Bosilovich MG, Reichle R, Wargan K, Coy L, Cullather R, Draper C, Akella S, Buchard V, Conaty A, da Silva AM, Gu W, Kim GK, Koster R, Lucchesi R, Merkova D, Nielsen JE, Partyka G, Pawson S, Putman W, Rienecker M, Schubert SD, Sienkiewicz M, Zhao B (2017) The modern-era retrospective analysis for research and applications, version 2 (MERRA-2). J Clim 30:5419–5454. CrossRefGoogle Scholar
  14. Giles DM, Holben BN, Tripathi SN, Eck TF, Newcomb WW, Slutsker I, Dickerson RR, Thompson AM, Mattoo S, Wang SH, Singh RP, Sinyuk A, Schafer JS (2011) Aerosol properties over the Indo-Gangetic Plain: a mesoscale perspective from the TIGERZ experiment. J Geophys Res Atmos 116:1–19. CrossRefGoogle Scholar
  15. Global Modeling and Assimilation Office (GMAO) (2015a), MERRA-2 tavg1_2d_flx_Nx: 2d,1-Hourly,Time-Averaged,Single-Level,Assimilation,Surface Flux Diagnostics V5.12.4, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: 20-10-2018.
  16. Global Modeling and Assimilation Office (GMAO) (2015b), MERRA-2 tavgM_2d_aer_Nx: 2d,Monthly mean, Time-averaged, Single-Level,Assimilation,Aerosol Diagnostics V5.12.4, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed: 20-10-2018.
  17. Guleria RP, Kuniyal JC (2013) Aerosol climatology in the northwestern Indian Himalaya: a study based on the radiative properties of aerosol. Air Qual Atmos Health 6:717–724. CrossRefGoogle Scholar
  18. Guleria RP, Kuniyal JC (2016) Characteristics of atmospheric aerosol particles and their role in aerosol radiative forcing over the northwestern Indian Himalaya in particular and over India in general. Air Qual Atmos Health 9:795–808. CrossRefGoogle Scholar
  19. Guttikunda SK, Carmichael GR, Calori G, Eck C, Woo JH (2003) The contribution of megacities to regional sulfur pollution in Asia. Atmos Environ 37:11–22. CrossRefGoogle Scholar
  20. Hoek G, Brunekreef B, Goldbohm S, Fischer P, van den Brandt PA (2002) Association between mortality and indicators of traffic-related air pollution in the Netherlands: a cohort study. Lancet 360:1203–1209CrossRefGoogle Scholar
  21. Hsu NC, Jeong M-J, Bettenhausen C, Sayer AM, Hansell R, Seftor CS, Huang J, Tsay SC (2013) Enhanced deep blue aerosol retrieval algorithm: the second generation. J Geophys Res Atmos 118:9296–9315. CrossRefGoogle Scholar
  22. Judd CM, McClelland GH, Ryan CS (2009) Data analysis - a model comparison approach. Routledge, AbingdonGoogle Scholar
  23. Kalapureddy MCR, Kaskaoutis DG, Ernest Raj P et al (2009) Identification of aerosol type over the Arabian Sea in the premonsoon season during the Integrated Campaign for Aerosols, Gases and Radiation Budget (ICARB). J Geophys Res Atmos 114:D17203. CrossRefGoogle Scholar
  24. Kaskaoutis DG, Kalapureddy MCR, Devara PCS, Kosmopoulos PG, Nastos PT, Krishna Moorthy K, Kambezidis HD (2009) Spatio-temporal aerosol optical characteristics over the Arabian Sea during the pre monsoon season. Atmos Chem Phys Discuss 9:22223–22269CrossRefGoogle Scholar
  25. Kaskaoutis DG, Kalapureddy MCR, Krishna Moorthy K, Devara PCS, Nastos PT, Kosmopoulos PG, Kambezidis HD (2010) Heterogeneity in pre-monsoon aerosol types over the Arabian Sea deduced from ship-borne measurements of spectral AODs. Atmos Chem Phys 10:4893–4908. CrossRefGoogle Scholar
  26. Kaskaoutis DG, Rashki A, Houssos EE, Legrand M, Francois P, Bartzokas A, Kambezidis HD, Dumka UC, Goto D, Takemura T (2017) Assessment of changes in atmospheric dynamics and dust activity over southwest Asia using the Caspian Sea-Hindu Kush Index. Int J Climatol 37:1013–1034. CrossRefGoogle Scholar
  27. Kedia S, Ramachandran S, Holben BN, Tripathi SN (2014) Quantification of aerosol type, and sources of aerosols over the Indo-Gangetic Plain. Atmos Environ 98:607–619. CrossRefGoogle Scholar
  28. Lau KM, Ramanathan V, Wu GX, Li Z, Tsay SC, Hsu C, Sikka R, Holben B, Lu D, Tartari G, Chin M, Koudelova P, Chen H, Ma Y, Huang J, Taniguchi K, Zhang R (2008) The joint aerosol-monsoon experiment: a new challenge for monsoon climate research. Bull Am Meteorol Soc 89:369–383. CrossRefGoogle Scholar
  29. Levy RC, Remer LA, Kleidman RG, Mattoo S, Ichoku C, Kahn R, Eck TF (2010) Global evaluation of the Collection 5 MODIS dark-target aerosol products over land. Atmos Chem Phys 10:10399–10420. CrossRefGoogle Scholar
  30. Li Z, Rosenfeld D, Fan J (2017) Aerosols and their impact on radiation, clouds, precipitation, and severe weather events. Oxford University Press, OxfordCrossRefGoogle Scholar
  31. McNoldy BD (2004) Surface winds, divergence, and vorticity in stratocumulus regions using QuikSCAT and reanalysis winds. Geophys Res Lett 31:L08105. CrossRefGoogle Scholar
  32. Ministry of Shipping (2016) Annual report 2016-17, Ministry of Shipping IndiaGoogle Scholar
  33. Misra A, Jayaraman A, Ganguly D (2015) Validation of version 5.1 MODIS aerosol optical depth (deep blue algorithm and dark target approach) over a semi-arid location in Western India. Aerosol Air Qual Res 15:252–262. CrossRefGoogle Scholar
  34. Monkkonen P (2004) Relationship and variations of aerosol number and PM10 mass concentrations in a highly polluted urban environment - New Delhi, India. Atmos Environ 38:425–433. CrossRefGoogle Scholar
  35. Moorthy KK, Satheesh SK (2000) Characteristics of aerosols over a remote island, Minicoy in the Arabian Sea: optical properties and retrieved size characteristics. Q J R Meteorol Soc 126:81–109. Google Scholar
  36. Nair VS, Suresh Babu S, Krishna Moorthy K (2008) Spatial distribution and spectral characteristics of aerosol single scattering albedo over the Bay of Bengal inferred from shipborne measurements. Geophys Res Lett 35:1–5. CrossRefGoogle Scholar
  37. Pease PP, Tchakerian VP, Tindale NW (1998) Aerosols over the Arabian Sea: geochemistry and source areas for aeolian desert dust. J Arid Environ 39:477–496. CrossRefGoogle Scholar
  38. Penner JE et al (2001) Aerosols, their direct and indirect effects. In: Houghton JT et al (eds) Climate change 2001: the scientific basis, contribution of working group I to the third assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, pp 289–348Google Scholar
  39. Platnick, S., et al., 2017. MODIS atmosphere L3 monthly product. NASA MODIS Adaptive Processing System, Goddard Space Flight Center, USA.
  40. Pope CA, Burnett RT, Thurston GD et al (2004) Cardiovascular mortality and long-term exposure to particulate air pollution. Circulation 109:71–77. CrossRefGoogle Scholar
  41. Prospero JM (2002) Environmental characterization of global sources of atmospheric soil dust identified with the NIMBUS 7 Total Ozone Mapping Spectrometer (TOMS) absorbing aerosol product. Rev Geophys 40:1002. CrossRefGoogle Scholar
  42. Quan J, Gao Y, Zhang Q, Tie X, Cao J, Han S, Meng J, Chen P, Zhao D (2013) Evolution of planetary boundary layer under different weather conditions, and its impact on aerosol concentrations. Particuology 11:34–40. CrossRefGoogle Scholar
  43. Rajeev K, Ramanathan V, Meywerk J (2000) Regional aerosol distribution and its long-range transport over the Indian Ocean. J Geophys Res Atmos 105:2029–2043. CrossRefGoogle Scholar
  44. Ramachandran S, Cherian R (2008) Regional and seasonal variations in aerosol optical characteristics and their frequency distributions over India during 2001–2005. J Geophys Res 113:D08207. Google Scholar
  45. Ramanathan V, Crutzen PJ, Andreae MO (1990) Biomass burning in the tropics: impact on atmospheric chemistry and biogeochemical cycles. Science 250:1669–1678. CrossRefGoogle Scholar
  46. Ramanathan V, Chung C, Kim D, Bettge T, Buja L, Kiehl JT, Washington WM, Fu Q, Sikka DR, Wild M (2005) Atmospheric brown clouds: impacts on South Asian climate and hydrological cycle. Proc Natl Acad Sci 102:5326–5333. CrossRefGoogle Scholar
  47. Rolph G, Stein A, Stunder B (2017) Real-time environmental applications and display system: READY. Environ Model Softw 95:210–228. CrossRefGoogle Scholar
  48. Sayer AM, Hsu NC, Bettenhausen C, Jeong M-J (2013) Validation and uncertainty estimates for MODIS Collection 6 “Deep Blue” aerosol data. J Geophys Res Atmos 118:7864–7872. CrossRefGoogle Scholar
  49. Schwartz SE (1996) The Whitehouse effect - shortwave radiative forcing of climate by anthropogenic aerosols: an overview. J Aerosol Sci 27:359–382. CrossRefGoogle Scholar
  50. Seinfeld JHJH, Pandis SNSN (2006) Atmospheric chemistry and physics: from air pollution to climate changeGoogle Scholar
  51. Singh RP, Dey S, Tripathi SN, Tare V, Holben B (2004) Variability of aerosol parameters over Kanpur, northern India. J Geophys Res Atmos 109:1–14. Google Scholar
  52. Srivastava N, Satheesh SK, Blond N, Moorthy KK (2016) Anthropogenic aerosol fraction over the Indian region: model simulations versus multi-satellite data analysis. Int J Remote Sens 37:782–804. CrossRefGoogle Scholar
  53. Stein AF, Draxler RR, Rolph GD, Stunder BJB, Cohen MD, Ngan F (2015) NOAA’s HYSPLIT atmospheric transport and dispersion modeling system. Bull Am Meteorol Soc 96:2059–2077. CrossRefGoogle Scholar
  54. Tanner PA, Law P (2002) Effect of synoptic weather systems upon the air quality in an Asian megacity. Water Air Soil Pollut 136:105–124. CrossRefGoogle Scholar
  55. Tripathi SN, Dey S, Chandel A, Srivastava S, Singh RP, Holben BN (2005) Comparison of MODIS and AERONET derived aerosol optical depth over the Ganga Basin, India. Ann Geophys 23:1093–1101. CrossRefGoogle Scholar
  56. Twomey S (1977) The influence of pollution on the shortwave albedo of clouds. J Atmos Sci 34:1149–1152CrossRefGoogle Scholar
  57. Wang C (2004) A modeling study on the climate impacts of black carbon aerosols. J Geophys Res Atmos 109:D3.
  58. Wang X, Wang K, Su L (2016) Contribution of atmospheric diffusion conditions to the recent improvement in air quality in China. Sci Rep 6:36404. CrossRefGoogle Scholar
  59. Washington R, Todd M, Middleton NJ, Goudie AS (2003) Dust-storm source areas determined by the total ozone monitoring spectrometer and surface observations. Ann Assoc Am Geogr 93:297–313. CrossRefGoogle Scholar
  60. WHO (2013) Research for universal health coverage: world health report 2013Google Scholar
  61. Zhao C, Wang Y, Yang Q et al (2010) Impact of East Asian summer monsoon on the air quality over China: view from space. J Geophys Res 115:D09301. Google Scholar
  62. Zheng XY, Fu YF, Yang YJ, Liu GS (2015) Impact of atmospheric circulations on aerosol distributions in autumn over eastern China: observational evidence. Atmos Chem Phys 15:12115–12138. CrossRefGoogle Scholar
  63. Ziomas IC, Melas D, Zerefos CS, Bais AF, Paliatsos AG (1995) Forecasting peak pollutant levels from meteorological variables. Atmos Environ 29:3703–3711. CrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Department of Applied Mechanics and HydraulicsNational Institute of Technology KarnatakaMangaloreIndia

Personalised recommendations