he primary objective of this project is to develop computer models that will improve the representation of growth rates of newly formed atmospheric particulate matter (referred to herewith as aerosol). This requires a better understanding of the role of organic compounds in the growth of 1 – 50 nm diameter aerosol. We shall accomplish this through analysis of DOE-funded observations and new laboratory experiments, resulting in both a complete understanding of the mechanisms of nanoparticle growth due to organic compounds and a semi-empirical representation for size-resolved growth rates. The latter will be integrated to regional and climate models to assess the role of new particle formation on climate.
We hypothesize is that a comprehensive model for the contribution of organics to nanoparticle growth rates requires knowledge of mechanisms that are involved in the following processes: (a) particulate phase chemistry between organic acids and bases; (b) particulate phase accretion product formation; and (c) direct partitioning of low-volatility gas-phase species. Our approach for developing this model starts with performing constrained box modeling of field observations from recent and planned DOE-funded field campaigns, which we believe will lead us to important insights into the species and mechanisms responsible for growth. This will be followed by laboratory experiments to explore the three mechanisms: (a) organic salt formation, (b) glyoxal reactive uptake, and (c) condensation of semivolatile organic compounds from the oxidation of biogenic organic compounds. Through the analysis of these field and laboratory observations, we will develop two models that represent the growth of atmospheric aerosol: the first is an integrative, extensible mechanistic model called the Mechanism for Aerosol Growth and Evolution (MAGE), which will include key gas-phase organic precursors as well as the mechanisms and rates by which they contribute to nanoparticle growth. The second is a semi-empirical “Aerosol Growth Rate Estimator” (AGRE), which will accept input parameters that are readily available in current-day regional and global climate models. We shall apply MAGE to the analysis of our DOE-funded observations to test our hypothesis as well as to direct us towards other processes that appear to play roles in nanoparticle growth. We shall integrate AGRE into GEOS-Chem-TOMAS global/regional chemical transport model to evaluate the semi-empirical model with DOE-funded atmospheric data. Finally, we will incorporate AGRE into the GISS-TOMAS Global Climate Model (GCM) with online aerosol microphysics. Using the GCM, we can evaluate impact of nucleation and organic-driven aerosol growth on climate forcing. The impact of the growth-model on the radiation budget of the GCM will be tested/constrained using ARM clear-sky and cloudy sky radiation data at the suite of ARM sites, and will result in a substantial improvement in the representation of particle size distributions in these models.
The potential impacts of this project include: (1) the identification all of the major organic species and processes that lead to nanoparticle growth, including the formation of organic salts; (2) parameterizations that can be used to predict the contribution of each partitioning mechanism to nanoparticle growth rates from local to global scales; (3) a numerical module for the growth of atmospheric aerosol that will be incorporated into regional and global atmospheric models; and (4) a more-accurate prediction and attribution of the role of new particle formation on clouds and climate.
