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Volume 13, No. 5, October 2013, Pages 1464-1474 PDF(1.61 MB)  
doi: 10.4209/aaqr.2013.02.0056   

Long-Term Measurement of Aerosol Number Size Distributions at Rural Background Station Košetice

Naděžda Zíková1,2, Vladimír Ždímal1

1 Department of Aerosol and Laser Studies, Institute of Chemical Processes Fundamentals of the Academy of Sciences of the Czech Republic, Rozvojova 135, 165 02 Prague, Czech Republic
2 Department of Meteorology and Environment Protection, Faculty of Mathematics and Physics, Charles University in Prague, V Holesovickach 2, 180 00 Prague, Czech Republic




Two years of SMPS data measured at the rural background station, Košetice observatory, are presented and statistically analyzed in this paper. The evaluation was performed on time scales ranging from years to days, and an overall new particle formation (NPF) frequency analysis was conducted as well. The annual average total concentration (integral value from 10 to 800 nm) was found to be 6.6 × 103 #/cm3, the particle number size distribution has a well expressed accumulation mode and high variability in particle sizes below 50 nm. In the seasonal data, particles of the smallest sizes (of diameters between 10 and 50 nm) had the high concentrations in summer, in contrast to the low concentrations found in winter. The particles of the largest sizes (over 300 nm) showed the opposite behavior. The analysis of NPF events revealed a strong annual cycle peaking in spring and summer and dropping in winter. In the monthly data, the global minimal of the total concentrations was recorded in December, and the global maximum in June. Weekly cycle analysis proved that the station is suitably characterized as a rural background – the weekly cycle was statistically insignificant on most days. The typical daily cycle of total concentrations showed its minimum between 3 and 6 AM, and its maximum at about 6 PM. Particles with diameters between 10 and 50 nm in diameter, compared to particles larger than 50 nm, exhibited higher daily amplitude.



Keywords: SMPS; Two-year time series; Rural background; Particle number size distributions.



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