Aerosol properties in atmosphere over Kyiv using lidar and sun-photometer observations

1Bovchaliuk, V, 2Milinevsky, G, 1Danylevsky, V, 3Goloub, Ph., 4Sosonkin, M, 1Yukhimchuk, Yu., 3Podvin, T
1Taras Shevchenko National University of Kyiv, Kyiv, Ukraine
2Main Astronomical Observatory of the National Academy of Sciences of Ukraine, Kyiv, Taras Shevchenko National University of Kyiv, Kyiv, Ukraine
3Laboratoire d’Optique Atmospherique, Lille1 University, Villeneuve d’Ascq, France
4Main astronomical observatory of the NAS of Ukraine, Kyiv, Ukraine
Space Sci.&Technol. 2017, 23 ;(6):34-45
https://doi.org/10.15407/knit2017.06.034
Publication Language: Ukrainian
Abstract: 
The article presents analysis of optical and microphysical aerosol properties, and their distribution in atmosphere over Kyiv city using lidar and sun-photometer observation at the beginning of September 2015. This period of time characterized with forest and peat fires nearby and at suburb of Kyiv. Observations were carried out with the CIMEL370 lidar and the sun-photometer of the AERONET Kyiv station located on the roof of the Main astronomical observatory of the NAS of Ukraine. The recently developed GARRLiC (Generalized Aerosol Retrieval from Radiometer and LIDAR Combined Data) algorithm was used for data analysis. It was established that at the beginning of the event (1-2 September) typical atmosphere with insignificant aerosol content was observed. A large amount of combustion products which increase aerosol content in several times has arrived into Kyiv from north-north-west direction starting from evening of 2 September. Range resolved aerosol properties were obtained in the first time for Ukraine region. Comparison with the corresponding values of aerosol properties obtained by the AERONET algorithm is made.
Keywords: aerosol, aerosol properties, forest and peat fires, height resolved aerosol distribution, lidar observations, photometric observations
References: 
 1. Yatskiv Ya. S., Mishhenko M. I., Rozenbush V. K. Proekt «Aerosol-UA»: distancionnoe zondirovanie ajerozolej v zemnoj atmosfere so sputnika [Project “Aerosol-UA”: remote sensing of aerosols in the Earth's atmosphere from a satellite]. Kosm. nauka tehnol., 18 (N 4), 3—15 (2012) [in Russian].
https://doi.org/10.15407/knit2012.04.003
2. Yatskiv Ya. S., Milinevsky G.P. Informatsiia pro zadymlenist' atmosfery v m. Kyievi [Information about smoky atmosphere in Kyiv city]. Visnyk Nat. akad. nauk Ukrainy [Visnyk of National Academy of Science of Ukraine], N 10, 25—30 (2015) [in Ukrainian].
3. Bovchaliuk A., Milinevsky G., Danylevsky V., et al. Variability of aerosol properties over Eastern Europe observed from ground and satellites in the period from 2003 to 2011. Atmos. Chem. Phys., 13 (N 13), 6587—6602 (2013) .
https://doi.org/10.5194/acp-13-6587-2013
4. Bovchaliuk V., Bovchaliuk A., Milinevsky G., et al. Aerosol Microtops II sunphotometer observations over Ukraine. Adv. Astron. and Space Phys., 3 (N 1), 46—52 (2013).
5. Bovchaliuk V., Goloub P., Podvin T., et al. Comparison of aerosol properties retrieved using GARRLiC, LIRIC, and Raman algorithms applied to multi-wavelength lidar and sun/sky-photometer data. Atmos. Meas. Techn., 9 (N 7), 3391—3405 (2016).
https://doi.org/10.5194/amt-9-3391-2016
6. Chin M., Diehl T., Tan Q., et al. Multi-decadal aerosol variations from 1980 to 2009: a perspective from observations and a global model. Atmos. Chem. Phys., 14, 3657— 3690 (2014).
https://doi.org/10.5194/acp-14-3657-2014
7. Draxler R. R., Hess G. D. An overview of the HYSPLIT_4 modelling system for trajectories. Austral. meteorological Mag., 47 (N 4), 295—308 (1998).
8. Dubovik O., Herman M., Holdak A., et al. Statistically optimized inversion algorithm for enhanced retrieval of aerosol properties from spectral multi-angle polarimetric satellite observations. Atmos. Meas. Techn., 4 (N 5), 975 (2011).
https://doi.org/10.5194/amt-4-975-2011
9. Dubovik O., Holben B., Eck T. F., et al. Variability of absorption and optical properties of key aerosol types observed in worldwide locations. J. Atmos. Sci., 59 (N 3), 590—608 (2002).
https://doi.org/10.1175/1520-0469(2002)059<0590:VOAAOP>2.0.CO;2
10. Dubovik O., King M. D. A flexible inversion algorithm for retrieval of aerosol optical properties from Sun and sky radiance measurements. J. Geophys. Res.: Atmospheres, 105D (N 16), 20673—20696 (2000).
https://doi.org/10.1029/2000JD900282 
11. Holben B. N., Eck T. F., Slutsker I., et al. AERONET—A federated instrument network and data archive for aerosol characterization. Remote Sens. Environ., 66 (N 1), 1—16 (1998).
https://doi.org/10.1016/S0034-4257(98)00031-5 
12. Klett J. D. Stable analytical inversion solution for processing lidar returns. Appl. Opt., 20 (N 2), 211—220 (1981).
https://doi.org/10.1364/AO.20.000211
13. Klett J. D. Lidar inversion with variable backscatter/extinction ratios. Appl. Opt., 24 (N 11), 1638—1643 (1985).
https://doi.org/10.1364/AO.24.001638 
14. Krueger A. J., Minzner R. A. A mid-latitude ozone model for the 1976 US Standard Atmosphere. J. Geophys. Res., 81 (N 24), 4477—4481 (1976).
https://doi.org/10.1029/JC081i024p04477 
15. Lenoble J., Remer L., Tanr D. (Eds). (2013). Aerosol remote sensing. Springer Science & Business Media. 
https://doi.org/10.1007/978-3-642-17725-5 
16. Lopatin A. Enhanced remote sensing of atmospheric aerosol by joint inversion of active and passive remote sensing observations (Doctoral dissertation, Lille 1) (2013)
17. Lopatin A., Dubovik O., Chaikovsky A., et al. Enhancement of aerosol characterization using synergy of lidar and sunphotometer coincident observations: the GARRLiC algorithm. Atmos. Meas. Techn., 6 (N 8), 2065—2088 (2013).
https://doi.org/10.5194/amt-6-2065-2013 
18. Milinevsky G., Danylevsky V., Bovchaliuk V., et al. Aerosol seasonal variations over urban sites in Ukraine and Belarus according to AERONET and POLDER measurements. Atmos. Meas. Techn. Discussions, 6(6), 10731—10759 (2013).
https://doi.org/10.5194/amtd-6-10731-2013 
19. Milinevsky G., Danylevsky V., Bovchaliuk V., et al. Aerosol seasonal variations over urban-industrial regions in Ukraine according to AERONET and POLDER measurements. Atmos. Meas. Techn., 7, 1459—1474 (2014).
https://doi.org/10.5194/amt-7-1459-2014 
20. Milinevsky G., Yatskiv Y., Degtyaryov O., et al. New satellite project Aerosol-UA: Remote sensing of aerosols in the terrestrial atmosphere. Acta Astronautica, 123, 292—300 (2016) 
https://doi.org/10.1016/j.actaastro.2016.02.027 
21. Mortier A., Goloub P., Podvin T., et al. Detection and characterization of volcanic ash plumes over Lille during the Eyjafjallajkull eruption. Atmos. Chem. Phys., 13 (N 7), 3705—3720 (2013) [in English].
https://doi.org/10.5194/acp-13-3705-2013 
22. Nicolae D., Nemuc A., Mller D., et al. Characterization of fresh and aged biomass burning events using multiwavelength Raman lidar and mass spectrometry. J. Geophys. Res.: Atmospheres, 118 (N 7), 2956—2965 (2013) [in English].
https://doi.org/10.1002/jgrd.50324 
23. Stocker T. et al. (Ed.). IPCC, 2013: Climate change 2013: the physical science basis: Working Group I contribution to the Fifth assessment report of the Intergovernmental Panel on Climate Change. 1535 p. (Cambridge University Press, Cambridge, 2014) [in English].
24. Weitkamp C. (Ed.). Lidar: range-resolved optical remote sensing of the atmosphere (Vol. 102). Springer Science & Business. (2006). [in English].