Sensitivity of Organic Aerosols to Meteorological Variables over North America: Interannual Variability as a Diagnostic for Climate-Air Quality Interactions

Abstract:

Organic aerosol (OA) comprises a large fraction of atmospheric fine particulate matter, impacting air quality and climate. Climate change is expected to impact the primary emission and the secondary production of OA, as well as its transport and removal in the atmosphere. However, it is extremely difficult to quantify these impacts or to validate the model predictions of such. Here we diagnosed the sensitivity of surface OA to the interannual variability of meteorological variables over North America. We used a chemical transport model, driven by assimilated meteorology and current-best emission estimates, to simulated surface OA during 1990-2013 and compared the results against observations from the IMPROVE dataset. Observations show large interannual variabilities in surface OA concentrations, as well as its sensitivity to temperature, precipitation, and regional wind. The model underestimates surface OA concentration over the eastern U.S. The model reproduces the observed correlation between surface OA and temperature, but severely underestimates the sensitivity of surface OA to temperature. This implies that a future warming climate will lead to greater surface OA concentration increases than currently predicted.