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Designing chemical mechanisms for ozone and secondary organic aerosol endpoints (ACM 2022)
Citation:
Pye, H., B. Place, Christine Allen, E. D'Ambro, Keith Wyat Appel, J. Bash, M. Coggon, S. Farrell, K. Foley, C. Hogrefe, W. Hutzell, F. McNeill, B. Murphy, I. Piletic, G. Pouliot, R. Schwantes, G. Sarwar, E. Saunders, K. Seltzer, H. Simon, W. Stockwell, L. Valin, F. Wisner, AND L. Xu. Designing chemical mechanisms for ozone and secondary organic aerosol endpoints (ACM 2022). Atmospheric Chemical Mechanisms, Davis, CA, December 07 - 09, 2022.
Impact/Purpose:
The new chemical mechanism, CRACMM, is being developed for use in CMAQ. CMAQ is used to develop state implementation plans and conduct regulatory analysis. The presentation will highlight how developing fine particle and ozone chemistry simultaneously has benefits.
Description:
Chemical mechanisms are traditionally designed to predict ozone and related gas-phase endpoints, and mass is often duplicated for purposes of predicting secondary organic aerosol (SOA). In this work, we use the recently developed Community Regional Atmospheric Chemistry Multiphase Mechanism (CRACMM) to show that coupling gas-phase radical chemistry and SOA formation can have benefits for representing the full range of atmospheric reactive organic carbon (ROC). We find that considering SOA and retaining intermediate and lower volatility emissions expands the coverage of primary ROC mass by 40%. In addition, considering SOA products in gas-phase mechanisms sequesters HOX, decreasing ozone formation compared to default assumptions. In cases where traditional gas-phase products were previously represented as smaller carbon-number products, consideration of SOA also improves conservation of carbon mass throughout the system. Furthermore, linking SOA formation to gas-phase products allows CRACMM to represent SOA precursors not included in earlier generation mechanisms. Newly included precursors, such as phenolic, furanone, and aldehyde species that are produced in later generations from species such as benzene and terpenes, further increase the amount of SOA that can be captured in models.