Constraining particle evolution from wall losses, coagulation, and condensation-evaporation in smog-chamber experiments: Optimal estimation based on size distribution measurements

A goal of secondary organic aerosol (SOA) experiments performed in smog chambers is to determine the condensation of SOA onto suspended particles. Complicating the calculation of the condensation rate are uncertainties in particle wall-loss rates. Wall-loss rates generally depend on particle size, turbulence in the bag, the size and shape of the bag, and particle charge. In analyzing smog-chamber data, some or all of the following assumptions are commonly made regarding the first-order wall-loss rate constant: (a) that it is constant during an experiment; (b) that it is constant between experiments; and (c) that it is not a strong function of particle size for the relatively narrow size distributions in smog chamber experiments. Each of these assumptions may not be justified in some circumstances. We present the development and evaluation of the Aerosol Parameter Estimation (APE) model. APE is an inverse model that solves the aerosol general dynamic equation to determine best estimates for the size-dependent condensation rate and size-dependent wall-loss rate as a function of time. Size distribution measurements from a Scanning Mobility Particle Sizer (SMPS) provide time boundary conditions that constrain the general dynamic equation. The APE model is tested using data from a smog chamber experiment with dry ammonium sulfate particles in which no condensation occurred. Finally, we assess the variability in predicted SOA production between different wall-loss correction methods for relatively-fast-chemistry limonene-ozonolysis experiments and relatively-slow-chemistry toluene-oxidation experiments. In the fast limonene experiments, wall-loss correction methods agree within 10% for SOA production, and in the slow toluene experiments, wall-loss correction methods disagree up to a factor of 2.