Characteristics of cluster mode particle number concentrations in India

Abstract

The dynamics of atmospheric aerosols is governed by the spatio-temporal variability in the particle number size distributions. Atmospheric new particle formation begins with the formation of the cluster mode (sub-3nm) particle number concentrations followed by their growth to large sizes in the atmosphere. Here, we used three years (2019-2022) particle number size distribution measurements in the size range from 1 to 3 nm from nano Condensation Nucleus Counter (nCNC) in Hyderabad, India. The distinct seasonal variation was observed in size-segregated cluster mode particle number concentrations, with the highest concentrations in spring (March-May) and the lowest concentrations in winter (December-February). The seasonal variability is strongly linked to the factors affecting cluster mode formation such as planetary boundary layer evolution, temperature (oxidation extent), pre-existing particles (coagulation sink), etc. The calculated sulfuric acid proxy is strongly correlated with cluster mode particle number concentrations and formation rates, indicating the important role of sulfuric acid in aerosol nucleation. The formation rate and growth rate of cluster mode particles were also the highest during spring than winter. Our analysis further revealed that cluster mode number concentrations were the highest at low particulate matter less than 2.5 µm (PM2.5) while it was the lowest at high PM2.5 levels, indicative of the efficient scavenging of cluster mode particles by large-size pre-existing particles. We have also used PARticle Growth And Nucleation (PARGAN) inversion model to estimate the formation rate and growth rate from particle size distribution measurements in the size range from 10 nm to 560 nm. We found that the estimated formation and growth rates from PARGAN model were compared with the measured formation and growth rates from nCNC, within the uncertainty levels. This underlines the applicability of PARGAN inversion model for estimating cluster mode formation and growth rates where such measurements are not available, particularly in India.