Theoretical and Applied Climatology

, Volume 115, Issue 3–4, pp 471–482 | Cite as

Some connections between aerosols, atmospheric transport, and relative humidity at peak Musala

  • Peter Nojarov
  • Ivo Kalapov
  • Jordan Stamenov
  • Todor Arsov
Original Paper


Some connections between aerosols, atmospheric transport, and relative humidity are investigated based on measurements at Basic Environmental Observatory (BEO) station, peak Musala (2,925 masl) for the period January 2009–January 2010. Data are chosen at 0:00 and 12:00 GMT every day. Main methods employed in this research are statistical—nonparametric tests of Mann–Whitney and Spearman. The main conclusion is that greater aerosol load at peak Musala is connected with transport of air masses from north to east horizon quarters. Bigger particles with longer lifetimes come from there. Air coming from the south horizon quarter is aerosol clearer. Relative humidity shows opposite distribution—higher values for transport from south horizon quarter. Correlation between this parameter and aerosols is negative with significant but small value. Distribution of blue, green, and red scattering and backscattering coefficients is similar to distribution of total aerosol concentration. Correlations between scattering and backscattering coefficients and total aerosol concentration are significant and positive. Courses of total aerosol concentration; diameter of particles with maximum concentration; and blue, green, and red scattering and backscattering coefficients have summer maximum and winter minimum. Diurnal course of total aerosol concentration in the two main seasons, winter (January) and summer (July), has day maximum and night minimum. Aerosols at peak Musala are predominantly of transparent or translucent type. The calculation of Ångström exponent α is more precise by using scattering coefficients. The nephelometers data could successfully characterize the haziness of the atmosphere above peak Musala.


Aerosol Optical Depth Aerosol Concentration Scanning Mobility Particle Sizer Winter Minimum Backscattering Coefficient 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors gratefully acknowledge the NOAA Air Resources Laboratory (ARL) for the provision of the HYSPLIT transport and dispersion model and/or READY website ( used in this publication. They also acknowledge the work of personnel of BEO station performed in very severe environmental conditions. Aerosol measurements would not be possible without financial support of FP7 EUSAAR project.


  1. Ångström AK (1964) The parameters of atmospheric turbidity. Tellus 16:64–75CrossRefGoogle Scholar
  2. Atmospheric Aerosol Properties and Climate Impacts, A report by the US Climate Change Science Program and the Subcommittee on Global Change Research (2009) M. Chin, R. A. Kahn, and S. E. Schwartz (eds.) National Aeronautics and Space Administration, Washington, DCGoogle Scholar
  3. Baltensperger U (2003) Aerosol measurements within the Global Atmosphere Watch programme. Observatoire de Montagne de Moussala OM2, fascicule 9: 35–40Google Scholar
  4. Damianova A, Penev I, Uzunov N, Lihareva N, Nikolova N, Sivriev I (2007) Monitoring of some trace elements in the air aerosols and environmental samples from peak Moussala area. Observatoire de Montagne de Moussala OM2, fascicule 12: 199–205Google Scholar
  5. Del Guasta M (2002) Daily cycles in urban aerosols observed in Florence (Italy) by means of an automatic 532–1064 nm LIDAR. Atmos Environ 36:2853–2865CrossRefGoogle Scholar
  6. Del Guasta M, Marini S (2000) On the retrieval of urban aerosol mass concentration by a 532 and 1064 nm LIDAR. J Aerosol Sci 31(12):1469–1488. doi: 10.1016/S0021-8502(00)00049-5 CrossRefGoogle Scholar
  7. Deleva AD, Peshev ZY, Slesar AS, Denisov S, Avramov LA, Stoyanov DV (2010) Vertical profiling of atmospheric backscatter with a Raman–aerosol LIDAR. AIP Conf Proc 1203:388–393CrossRefGoogle Scholar
  8. Draxler RR, Rolph GD (2003) HYSPLIT (HYbrid Single-Particle Lagrangian Integrated Trajectory) model access via NOAA ARL READY website ( NOAA Air Resources Laboratory, Silver Spring, MD
  9. Dubovik O, Holben B, Eck TF, Smirnov A, Kaufman YJ, King MD, Tanre D, Slutsker I (2002) Variability of absorption and optical properties of key aerosol types observed in worldwide locations. J Atmos Sci 59:590–607CrossRefGoogle Scholar
  10. Kalapov I (2007) Meteorological measurements at the Basic Environmental Observatory “Moussala”. Observatoire de Montagne de Moussala OM2, fascicule 12: 56–63Google Scholar
  11. Kolev I, Parvanov O, Kaprielov B, Donev E, Ivanov D (1998) LIDAR observations of sea-breeze and land-breeze aerosol structure on the Black Sea. J Appl Meteorol 37(10):982–995CrossRefGoogle Scholar
  12. Kolev I, Skakalova T, Grigorov I (2000) LIDAR measurement of the aerosol extinction profile in Black Sea coastal zone. Atmos Environ 34(22):3813–3822CrossRefGoogle Scholar
  13. Kosmopoulos PG, Kaskaoutis DG, Nastos PT, Kambezidis HD (2008) Seasonal variation of columnar aerosol optical properties over Athens, Greece, based on MODIS data. Remote Sens Environ 112(5):2354–2366CrossRefGoogle Scholar
  14. Penev I, Drenska M, Damyanov B, Valova Tsc (2007) Monitoring of the aerosols radioactivity at BEO—“Moussala”. Observatoire de Montagne de Moussala OM2, fascicule 12: 194–198Google Scholar
  15. Peshev ZY, Deleva AD, Dreischuh TN, Stoyanov DV (2010) LIDAR measurements of atmospheric dynamics over high mountainous terrain. AIP Conf Proc 1203:1108–1113CrossRefGoogle Scholar
  16. Peshev ZY, Dreischuh TN, Toncheva EN, Stoyanov DV (2012) Two-wavelength LIDAR characterization of atmospheric aerosol fields at low altitudes over heterogeneous terrain. J Appl Remote Sens 6:063581CrossRefGoogle Scholar
  17. Savov PB, Skakalova TS, Kolev IN, Ludwig FL (2002) LIDAR investigation of the temporal and spatial distribution of atmospheric aerosols in mountain valleys. J Appl Meteorol 41(5):528–541CrossRefGoogle Scholar
  18. Seinfeld J, Pandis S (2006) Atmospheric chemistry and physics: from air pollution to climate change (second edition ed.). Wiley, HobokenGoogle Scholar
  19. Solomon S, Qin D, Manning M, Alley RB, Berntsen T, Bindoff NL, Chen Z, Chidthaisong A, Gregory JM, Hegerl GC, Heimann M, Hewitson B, Hoskins BJ, Joos F, Jouzel J, Kattsov V, Lohmann U, Matsuno T, Molina M, Nicholls N, Overpeck J, Raga G, Ramaswamy V, Ren J, Rusticucci M, Somerville R, Stocker TF, Whetton P, Wood RA, Wratt D (2007) Technical summary. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) Climate change 2007: the physical science basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, CambridgeGoogle Scholar
  20. Venzac H, Sellegri K, Villani P, Picard D, Laj P (2009) Seasonal variation of aerosol size distributions in the free troposphere and residual layer at the puy de Dôme station, France. Atmos Chem Phys 9:1465–1478CrossRefGoogle Scholar
  21. Weingartner E, Nyeki S, Baltensperger U (1999) Seasonal and diurnal variation of aerosol size distributions (10 < D < 750 nm) at a high-alpine site (Jungfraujoch 3580 masl). J Geophys Res-Atmos 104(D21):26809–26820CrossRefGoogle Scholar
  22. World Meteorological Organization (1990) On the statistical analysis of series of observations. Technical note 143/WMO 415, GenevaGoogle Scholar
  23. Zhou M, Yu H, Dickinson RE, Dubovik O, Holben BN (2005) A normalized description of the direct effect of key aerosol types on solar radiation as estimated from Aerosol Robotic Network aerosols and Moderate Resolution Imaging Spectroradiometer albedos. Journal of Geophysical Research, Volume 110, Issue D19, doi: 10.1029/2005JD005909

Copyright information

© Springer-Verlag Wien 2013

Authors and Affiliations

  • Peter Nojarov
    • 1
  • Ivo Kalapov
    • 2
  • Jordan Stamenov
    • 2
  • Todor Arsov
    • 2
  1. 1.National Institute of Geophysics, Geodesy and Geography, Bulgarian Academy of SciencesSofiaBulgaria
  2. 2.Institute of Nuclear Research and Nuclear Energy, Bulgarian Academy of SciencesSofiaBulgaria

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