An improved criterion for new particle formation in diverse atmospheric environments

C Kuang,I Riipinen,A V Mccormick,M Kulmala,S.-L Sihto,P H Mcmurry

doi:10.5194/acp-10-8469-2010

Abstract

Abstract. A dimensionless theory for new particle formation (NPF) was developed, using an aerosol population balance model incorporating recent developments in nucleation rates and measured particle growth rates. Based on this theoretical analysis, it was shown that a dimensionless parameter LΓ, characterizing the ratio of the particle scavenging loss rate to the particle growth rate, exclusively determined whether or not NPF would occur on a particular day. This parameter determines the probability that a nucleated particle will grow to a detectable size before being lost by coagulation with the pre-existing aerosol. Cluster-cluster coagulation was shown to contribute negligibly to this survival probability under conditions pertinent to the atmosphere. Data acquired during intensive measurement campaigns in Tecamac (MILAGRO), Atlanta (ANARChE), Boulder, and Hyytiälä (QUEST II, QUEST IV, and EUCAARI) were used to test the validity of LΓ as an NPF criterion. Measurements included aerosol size distributions down to 3 nm and gas-phase sulfuric acid concentrations. The model was applied to seventy-seven NPF events and nineteen non-events (characterized by growth of pre-existing aerosol without NPF) measured in diverse environments with broad ranges in sulfuric acid concentrations, ultrafine number concentrations, aerosol surface areas, and particle growth rates (nearly two orders of magnitude). Across this diverse data set, a nominal value of LΓ=0.7 was found to determine the boundary for the occurrence of NPF, with NPF occurring when LΓ<0.7 and being suppressed when LΓ>0.7. Moreover, nearly 45% of measured LΓ values associated with NPF fell in the relatively narrow range of 0.1

Highlights

Atmospheric aerosols contribute significantly to the net radiative forcing that drives the earth’s energy balance, directly through the scattering and absorption of incident solar radiation, and indirectly through their role as potential cloud condensation nuclei (CCN) (Charlson et al, 1992)
We have developed a new aerosol population balance model that predicts new particle formation in a time-dependent system, incorporating recent developments in nucleation rates, parameterizing them as power-law functions of sulfuric acid concentration, (Kulmala et al, 2006; Sihto et al, 2006; Riipinen et al, 2007; Kuang et al, 2008), and recent work in determining the contribution of sulfuric acid condensation to measured nanoparticle growth rates (Birmili et al, 2003; Stolzenburg et al, 2005; Sihto et al, 2006; Riipinen et al, 2007; Iida et al, 2008b)
Relevant model inputs were obtained from measured aerosol size distributions and [H2SO4] for each analyzed new particle formation (NPF) event and are listed in Table 1:, Nm, and AFuchs (Fuchs aerosol surface area averaged over duration of NPF event)

Summary

Introduction

Atmospheric aerosols contribute significantly to the net radiative forcing that drives the earth’s energy balance, directly through the scattering and absorption of incident solar radiation, and indirectly through their role as potential cloud condensation nuclei (CCN) (Charlson et al, 1992). New particle formation (NPF), an important source of atmospheric particles, occurs frequently in diverse locations (Kulmala et al, 2004b), and is an important source of CCN, as demonstrated in various measurement campaigns (Kerminen et al, 2005; Laaksonen et al, 2005) and modeling efforts (Spracklen et al, 2008; Kuang et al, 2009). Since the highest uncertainties in the current estimates for global radiative forcing are associated with these direct and indirect aerosol effects (Chin et al, 2009), it is essential to understand processes that determine new particle formation (NPF) rates. NPF occurs when nucleated particles grow to a size that can be detected. While nucleation potentially occurs every day, NPF only occurs when particle growth to the detection limit

Methods

Results

Conclusion