Chemical transport models often underestimate inorganic aerosol acidity in remote regions of the atmosphere

Nault, Benjamin A., Campuzano-Jost, Pedro, Day, Douglas A., Jo, Duseong S., Schroder, Jason C., Allen, Hannah M., Bahreini, Roya, Bian, Huisheng, Blake, Donald R., Chin, Mian, Clegg, Simon L., Colarco, Peter R., Crounse, John D., Cubison, Michael J., Decarlo, Peter F., Dibb, Jack E., Diskin, Glenn S., Hodzic, Alma, Hu, Weiwei, Katich, Joseph M., Kim, Michelle J., Kodros, John K., Kupc, Agnieszka, Lopez-Hilfiker, Felipe D., Marais, Eloise A., Middlebrook, Ann M., Andrew Neuman, J., Nowak, John B., Palm, Brett B., Paulot, Fabien, Pierce, Jeffrey R., Schill, Gregory P., Scheuer, Eric, Thornton, Joel A., Tsigaridis, Kostas, Wennberg, Paul O., Williamson, Christina J. and Jimenez, Jose L. (2021) Chemical transport models often underestimate inorganic aerosol acidity in remote regions of the atmosphere. Communications Earth & Environment, 2. ISSN 2662-4435

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Abstract

The inorganic fraction of fine particles affects numerous physicochemical processes in the atmosphere. However, there is large uncertainty in its burden and composition due to limited global measurements. Here, we present observations from eleven different aircraft campaigns from around the globe and investigate how aerosol pH and ammonium balance change from polluted to remote regions, such as over the oceans. Both parameters show increasing acidity with remoteness, at all altitudes, with pH decreasing from about 3 to about −1 and ammonium balance decreasing from almost 1 to nearly 0. We compare these observations against nine widely used chemical transport models and find that the simulations show more scatter (generally R2 < 0.50) and typically predict less acidic aerosol in the most remote regions. These differences in observations and predictions are likely to result in underestimating the model-predicted direct radiative cooling effect for sulfate, nitrate, and ammonium aerosol by 15–39%.

Item Type: Article
Additional Information: Funding Information: This work was supported by NASA grants NNX15AH33A, NNX15AJ23G, 80NSSC19K0124, 80NSSC18K0630, NNX15AG61A, NSF grants 1360745, 1652688, and DOE (BER/ASRprogram) DE-SC0016559. We would like to acknowledge high-performance computing support from Cheyenne (doi:10.5065/D6RX99HX) provided by NCAR’s Computational and Information Systems Laboratory, sponsored by the National Sciences Foundation.
Uncontrolled Keywords: earth and planetary sciences(all),environmental science(all) ,/dk/atira/pure/subjectarea/asjc/1900
Faculty \ School: Faculty of Science > School of Environmental Sciences
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Depositing User: LivePure Connector
Date Deposited: 26 Jul 2022 09:30
Last Modified: 12 Aug 2022 06:45
URI: https://ueaeprints.uea.ac.uk/id/eprint/86855
DOI: 10.1038/s43247-021-00164-0

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