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© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 30 Nov 2018

Research article | 30 Nov 2018

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This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Chemistry and Physics (ACP).

Interrelations between surface, boundary layer, and columnar aerosol properties over a continental urban site

Dongxiang Wang, Dominika Szczepanik, and Iwona S. Stachlewska Dongxiang Wang et al.
  • University of Warsaw, Faculty of Physics, Institute of Geophysics, Warsaw, 02-093, Poland

Abstract. PollyXT Raman Polarization Lidar observations were performed at the Remote Sensing laboratory in Warsaw (52.2109° N, 20.9826° E), Poland, in the framework of the European Aerosol Research Lidar Network (EARLINET) and the Aerosols, Clouds and Trace gases Research Infrastructure (ACTRIS). Data collected in July, August and September of 2013, 2015 and 2016 were analysed using the classical Raman approach. In total 202 sets of profiles of the particle extinction and backscatter coefficient, and linear particle depolarization ratio at 355 nm and 532 nm were derived for statistical investigations (EARLINET/ACTRIS Data Base). The main analysis was focused on intensive optical properties obtained within aerosol boundary layer (ABL). The interrelationships of different optical properties inside ABL are discussed for different periods: entire day, nocturnal time and sunrise/sunset time. In addition, the lidar derived boundary layer optical properties were compared with the columnar daytime aerosol properties derived from radiometer (MFR-7, PolandAOD-NET) and photometer (C318, AERONET). Relationships of these and surface in-situ measurements of particulate matter with an aerodynamic diameter < 10 μm (PM10) and < 2.5 μm (PM2.5) (WIOŚ Network) are investigated. Within boundary layer, the lidar derived optical properties (entire day, 202 sets) revealed the mean aerosol optical depth (AODABL) of 0.27 ± 0.17 at 355 nm and 0.15 ± 0.10 at 532 nm; the mean Ångström exponent (ÅEABL) of 1.65 ± 0.45; the mean lidar ratio (LRABL) of 49 ± 16 sr at 355 nm and 41 ± 15 sr at 532 nm; the mean linear particle depolarization ratio (PLDRABL) of 0.02 ± 0.01 at 355 nm and 0.05 ± 0.02 at 532 nm, the mean water vapor mixing ratio (WVMRABL) of 8.16 ± 2.40 g/kg. Aerosol composition within ABL was assessed based on the derived properties interpreted with respect to values reported in literature and backward trajectories; it consisted either of pure urban anthropogenic pollution aerosols (~ 60 %), its mixtures with biomass burning aerosols (< 12 %), pollen (< 8 %) or marine particles (< 6 %). No significant contribution of mineral dust in boundary layer was found. In summer and early-autumn in Warsaw, the lidar derived aerosol boundary layer height (ABLH) and the columnar radiometer/photometer AODCL show negative correlations (−0.6 to −0.7), attributed to likely influence of smoke, pollution and dust suspended in aerosol layers in the free troposphere, while the ABLH and the lidar derived AODABL exhibit positive correlation (~ 0.6), attributed in majority cases to local anthropogenic pollution. LRABL and surface fine to coarse mass ratio (FCMR) presents weak positive-correlation (~ 0.4) at nocturnal time, due to the higher(lower) occurrence of fine(coarse) particles at night. On the contrary, weak negative-correlation (~ −0.3) of LRABL and FCMR are present in sunrise/sunset time, for inverse occurrence of fine and coarse particles. A negative-correlation of PLDRABL and FCMR (~ −0.4 at 355 nm, −0.6 to −0.7 at 532 nm) for all time period and no relation between PLDRABL and ÅEABL (~ 0.05) was found. Relation of AODABL and PM10 reveals positive correlation (0.4 355; 0.5 532) for sunrise/sunset time, but no significant correlations found for AODABL and PM2.5 (0.26 at 355; 0.16 at 532 nm). In general, a positive correlation of AODABL and LRABL (stronger pronounced at 355 nm) and a negative correlation ÅEABL and LRABL (stronger pronounced at 532 nm) is observed. The ÅECL values stay roughly between 1.0 and 2.0, while the ÅEABL values range from 0.1 to 2.5, indicating a variety of particle sizes occurring inside ABL during summer and early-autumn period in Warsaw.

Dongxiang Wang et al.
Interactive discussion
Status: final response (author comments only)
Status: final response (author comments only)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Dongxiang Wang et al.
Data sets

The EARLINET publishing group 2000-2015; EARLINET All 2000-2015. World Data Center for Climate (WDCC) at DKRZ K. Acheson, M. Adam, L. Alados-Arboledas, D. Althausen, F. Amato, V. Amiridis, A. Amodeo, A. Ansmann, A. Apituley, Y. Arshinov, H. Baars, D. Balis, R. Barragán, O. Batet, L. Belegante, I. Binietoglou, S. Bobrovnikov, S. Bohlmann, D. Bortoli, A. Boselli, J. Bösenberg, J. A. Bravo-Aranda, P. Burlizzi, E. Carstea, A. Chaikovsky, P. Claramunt, A. Comerón, G. D'Amico, D. Daou, M. de Graaf, F. De Tomasi, A. Deleva, T. Dreischuh, R. Engelmann, M. Filioglou, F. Finger, V. Freudenthaler, P. Freville, A. J. Fernandez García, D. Garcia-Vizcaino, M. Gausa, A. Geiß, E. Giannakaki, H. Giehl, A. Giunta, M. J. Granados-Muñoz, M. Grein, I. Grigorov, S. Groß, C. Gruening, J. L. Guerrero-Rascado, D. Hadjimitsis, A. Haefele, M. Haeffelin, I. Hanssen, T. Hayek, M. Iarlori, T. Kanitz, P. Kokkalis, M. Komppula, D. Kumar, D. Lange, H. Linné, M. A. Lopez, F. Madonna, R.-E. Mamouri, G. Martucci, V. Matthias, I. Mattis, F. Molero Menéndez, V. Mitev, L. Mona, N. Montoux, Y. Morille, A. Müller, D. Müller, C. Muñoz-Porcar, M. Mylonaki, F. Navas-Guzmán, A. Nemuc, D. Nicolae, M. Pandolfi, N. Papagiannopoulos, A. Papayannis, G. Pappalardo, M. R. Perrone, Z. Peshev, C. Pietras, A. Pietruczuk, G. Pisani, C. Potma, J. Preißler, M. Pujadas, J. P. Putaud, C. Radu, F. Ravetta, M. M. Md. Reba, A. Reigert, V. Rizi, F. Rocadenbosch, A. Rodríguez-Gómez, M. Rosoldi, A. A. Ruth, L. Sauvage, J. Schmidt, F. Schnell, A. Schwarz, P. Seifert, I. Serikov, M. Sicard, A. M. Silva, V. Simeonov, N. Siomos, T. Sirch, N. Spinelli, I. S. Stachlewska, D. Stoyanov, D. Szczepanik, C. Talianu, M. Tesche, S. Tomás, T. Trickl, H. Volten, K.-A. Voudouri, F. Wagner, U. Wandinger, X. Wang, M. Wiegner, and K. M. Wilson

Dongxiang Wang et al.
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