Particle number to volume concentration ratios at two measurement sites in Finland

被引:3
作者
Kivekas, Niku
Kerminen, Veli-Matti
Engler, Christa
Lihavainen, Heikki
Komppula, Mika
Viisanen, Yrjo
Kulmala, Markku
机构
[1] Finnish Meteorol Inst, Res & Dev, FIN-00101 Helsinki, Finland
[2] Univ Helsinki, Dept Phys Sci, FIN-00014 Helsinki, Finland
关键词
D O I
10.1029/2006JD007102
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
Past studies have indicated that the aerosol number to volume concentration ratio R, defined as the number concentration of particles larger than a certain cutoff diameter divided by the total particle volume concentration, shows little variability in marine conditions. In this study, aerosol number size distributions from Pallas in northern Finland and from the island of Uto in the Baltic Sea, representing more continental aerosol systems, were analyzed. The data set covered continuous measurements for 20 months at Pallas and 21 months at Uto. The average value and standard deviation of R, calculated from the measured data, were found to be inversely dependent on the cutoff diameter used, d(c). The average value of R (in mm(-3)) could be expressed as R(d(c)) = 22,000 x d(c)(-1) + 20 (where d(c) is in nm) in Pallas and R(d(c)) = 40,000 x d(c)(-1) - 160 in Uto in dc range 50 - 200 nm. Also, the relative deviation ( standard deviation divided by average value) of R( dc) was found to be dependent on the cutoff diameter. A clear seasonal pattern of the values of R was observed at both sites, and this was found to be related to ambient temperature. The value of R was found to depend on the air mass type at Pallas, but at Uto such dependency was not observed. Besides temperature, R was also analyzed against several meteorological parameters, including global solar radiation, air pressure, relative humidity, and rain. The found dependencies between the number of potential cloud condensation nuclei and particle volume concentration provide tools for developing more accurate empirical parameterizations describing cloud formation in large-scale atmospheric models.
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页数:13
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