Particle growth kinetics over the Amazon rainforest
Abstract
Aerosol particles larger than 100 nm play a key role in global climate by acting as cloud condensation nuclei (CCN). Most of these particles, originated from new particle formation or directly emitted into the atmospheric, are initially too small to serve as CCN. These small particles grow to CCN size mainly through condensation of secondary species. In one extreme, the growth is dictated by kinetic condensation of very low-volatility compounds, favoring the growth of the smallest particles; in the other extreme, the process is driven by Raoult's law-based equilibrium partitioning of semi-volatile organic compound, favoring the growth of larger particles. These two mechanisms can lead to very different production rates of CCN. The growth of particles depends on a number of parameters, including the volatility of condensing species, particle phase, and diffusivity inside the particles, and this process is not well understood in part due to lack of ambient data. Here we examine atmospheric particle growth using high-resolution size distributions measured onboard the DOE G-1 aircraft during GoAmazon campaign, which took place from January 2014 to December 2015 near Manaus, Brazil, a city surrounded by natural forest for over 1000 km in every direction. City plumes are clearly identified by the strong enhancement of nucleation and Aitken mode particle concentrations over the clean background. As the plume traveled downwind, particle growth was observed, and is attributed to condensation of secondary species and coagulation (Fig.1). Observed aerosol growth is modeled using MOSAIC (Model for Simulating Aerosol Interactions and Chemistry), which dynamically partitions multiple compounds to all particle size bins by taking into account compound volatility, gas-phase diffusion, interfacial mass accommodation, particle-phase diffusion, and particle-phase reaction. The results from both wet and dry seasons will be discussed.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2016
- Bibcode:
- 2016AGUFM.A43E0289P
- Keywords:
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- 3311 Clouds and aerosols;
- ATMOSPHERIC PROCESSESDE: 3355 Regional modeling;
- ATMOSPHERIC PROCESSESDE: 0426 Biosphere/atmosphere interactions;
- BIOGEOSCIENCES