Long-Term Field Observations Lead to New Insights in the Formation of Organic Aerosols

  • 24 November 2020
Long-Term Field Observations Lead to New Insights in the Formation of Organic Aerosols

The Clean Air Act Amendments of 1990 have resulted in a significant decline in ambient aerosol in the US, mostly due to reduced emissions leading to reductions in inorganic aerosol. These reductions in inorganic aerosols, however, mean organic aerosols (OA) now constitute the majority of fine particulate matter in the southeastern US, especially in the summer. Organic aerosols, which are both directly emitted by combustion processes (primary OA) and form indirectly in the atmosphere (secondary OA), can strongly impact air quality, regional climate, and human welfare. The US southeast is a prime spot for secondary OA formation due to being one of the largest biogenic volatile organic compound (BVOC) emission hotspots in the world, along with large anthropogenic emissions of pollutants. BVOCs often, but not always, lead to the formation of secondary OA. Long-term field measurements show a decreasing trend in OA in the southeastern US, though different atmospheric models attribute this decrease to different drivers. This study, published in Atmospheric Chemistry and Physics, uses observations from three surface networks to examine the long-term trend and the month-to-month variations in OA in the southeastern US from 2000-2013.

Dr.Jingqiu Mao, University of Alaska Fairbanks, and Dr. Nga Lee Ng, Georgia Institute of Technology, were both funded under the Atmospheric Chemistry, Carbon Cycle, & Climate (AC4) 2018 program “Formation of Aerosols from Biogenic Emissions.” Together, along with a team of collaborators, Mao and Ng investigated how the same trends were represented in a 3D chemical transport model. While the network observations showed a slow decrease in total OA over time, the model showed a much faster decrease in OA over the same time period and much more month-to-month variability. The research team were surprised to find that month-to-month changes in observed OA were far smaller than modeled. They explain why and how the model might differ from the network observations (which has to do with the biogenic formation of secondary OA from a specific type of BVOC) and offer their suggestions on how to correct the difference. As their modifications do not completely correct the discrepancies between model and observations, the authors also point to potenital future areas of improvement. 

Overall, this study provides new insights into the formation of secondary OA, which drives the month-to-month variability of OA. Remarkably, these insights come from field observations and not complex mass spectrometers, resulting in a large gain at the level of fundamental chemical mechanisms from a relatively simple starting point.

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