Improved Prediction of In-Cloud Biogenic SOA: Experiments and CMAQ Model RefinementsEPA Grant Number: R833751
Title: Improved Prediction of In-Cloud Biogenic SOA: Experiments and CMAQ Model Refinements
Investigators: Turpin, Barbara , Seitzinger, Sybil
Institution: Rutgers, The State University of New Jersey
EPA Project Officer: Chung, Serena
Project Period: November 1, 2007 through August 31, 2010 (Extended to October 31, 2011)
Project Amount: $598,544
RFA: Sources and Atmospheric Formation of Organic Particulate Matter (2007) RFA Text | Recipients Lists
Research Category: Air Quality and Air Toxics , Particulate Matter , Air
Laboratory experiments and modeling will be performed to enable better prediction of secondary organic aerosol formation through cloud processing and to facilitate the development of more effective air quality management strategies.
Hypothesis: In-cloud secondary organic aerosol (SOA) formation is under-predicted by recent cloud chemistry simulations, which include only the SOA contribution of low volatility organic acids and use chemical mechanisms with assumed pathways and products. Also, the yields and composition of in-cloud SOA are altered by the presence of HNO3. Furthermore, in certain U.S. regions, in-cloud SOA formed from biogenic hydrocarbons (i.e., “biogenic SOA”) can be reduced by decreasing anthropogenic precursors of H2O2 and HNO3. Objectives: 1) Develop mechanistic/ kinetic data needed to simulate in-cloud SOA formation in the presence of HNO3, 2) Identify conditions for which predicted in-cloud SOA formed from isoprene decreases with reductions in interstitial concentrations of H2O2 and HNO3, and 3) Incorporate an in-cloud SOA formation pathway into the Community Multiscale Air Quality (CMAQ) model and explore the magnitude of in-cloud SOA formation through a limited set of model simulations.
1) We will update the Lim cloud chemistry model to include mechanistic/ kinetic data from our recent aqueous photooxidation experiments with water-soluble (second generation) products of isoprene oxidation and H2O2, a major photochemical source of •OH in clouds [i.e., methylglyoxal (MG) pyruvic acid (PA) and glyoxal (GLY)] 2) We will conduct (and incorporate results from) aqueous GLY and MG photooxidation experiments with HNO3, another major photochemical source of •OH and the predominant source of nitrogen radicals in clouds. Through chemical analysis and reaction vessel kinetic modeling, these experiments will identify/characterize products, refine the chemical mechanism and expand the kinetic data available for use in cloud chemistry and air quality models. We anticipate that HNO3 will contribute to the yield of in-cloud SOA through ion, radical and acid-catalyzed reactions that form low volatility organic-nitrogen compounds, organic acids, multi-functional alcohols and oligomers. 3) The updated Lim cloud chemistry model will be used to explore the sensitivity of in-cloud SOA formation from isoprene on interstitial gas phase concentrations of H2O2 and HNO3, atmospheric oxidants with anthropogenic precursors. Since HNO3 is a ubiquitous cloud water component, this work will improve prediction of in-cloud SOA formation. This is an important step toward understanding when/where reductions in in-cloud “biogenic SOA” concentrations can be achieved through reductions in anthropogenic emissions. 4) The CMAQ aqueous phase chemistry module will be revised to include in-cloud SOA formation. The CMAQ model will be used to conduct a limited number of simulations for the continental United States with and without organic cloud chemistry. Products and findings will be made widely available.
: 1) A better understanding of in-cloud SOA formation including dependence of “biogenic SOA” on anthropogenic precursors (RFA goal #1,3). 2) More accurate prediction of organic PM from emissions (RFA goal #2). Note: Current air quality models do not include multiphase SOA formation pathways and severely under-predict ambient organic PM concentrations. 3) More accurate air quality management tools (i.e., CMAQ).