Size and time-resolved growth rate measurements of 1 to 5 nm freshly formed atmospheric nuclei
This study presents measurements of size and time-resolved particle diameter growth rates for freshly nucleated particles down to 1 nm geometric diameter. Novel data analysis methods were developed, de-coupling for the first time the size and time-dependence of particle growth rates by fitting the aerosol general dynamic equation to size distributions obtained at an instant in time. Size distributions of freshly nucleated total aerosol (neutral and charged) were measured during two intensive measurement campaigns in different environments (Atlanta, GA and Boulder, CO) using a recently developed electrical mobility spectrometer with a diethylene glycol-based ultrafine condensation particle counter as the particle detector. One new particle formation (NPF) event from each campaign was analyzed in detail. At a given instant in time during the NPF event, size-resolved growth rates were obtained directly from measured size distributions and were found to increase approximately linearly with particle size from ~1 to 3 nm geometric diameter, increasing from 5.5 ± 0.8 to 7.6 ± 0.6 nm h −1 in Atlanta (13:00) and from 5.6 ± 2 to 27 ± 5 nm h −1 in Boulder (13:00). The resulting growth rate enhancement Γ, defined as the ratio of the observed growth rate to the growth rate due to the condensation of sulfuric acid only, was found to increase approximately linearly with size from ~1 to 3 nm geometric diameter. For the presented NPF events, values for Γ had lower limits that approached ~1 at 1.2 nm geometric diameter in Atlanta and ~3 at 0.8 nm geometric diameter in Boulder, and had upper limits that reached 8.3 at 4.1 nm geometric diameter in Atlanta and 25 at 2.7 nm geometric diameter in Boulder. Nucleated particle survival probability calculations comparing the effects of constant and size-dependent growth indicate that neglecting the strong dependence of growth rate on size from 1 to 3 nm observed in this study could lead to a significant overestimation of CCN survival probability.