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Published October 25, 2016 | Supplemental Material + Published
Journal Article Open

Reduced anthropogenic aerosol radiative forcing caused by biogenic new particle formation


The magnitude of aerosol radiative forcing caused by anthropogenic emissions depends on the baseline state of the atmosphere under pristine preindustrial conditions. Measurements show that particle formation in atmospheric conditions can occur solely from biogenic vapors. Here, we evaluate the potential effect of this source of particles on preindustrial cloud condensation nuclei (CCN) concentrations and aerosol–cloud radiative forcing over the industrial period. Model simulations show that the pure biogenic particle formation mechanism has a much larger relative effect on CCN concentrations in the preindustrial atmosphere than in the present atmosphere because of the lower aerosol concentrations. Consequently, preindustrial cloud albedo is increased more than under present day conditions, and therefore the cooling forcing of anthropogenic aerosols is reduced. The mechanism increases CCN concentrations by 20–100% over a large fraction of the preindustrial lower atmosphere, and the magnitude of annual global mean radiative forcing caused by changes of cloud albedo since 1750 is reduced by 0.22 W m^(−2) (27%) to −0.60 W m^(−2). Model uncertainties, relatively slow formation rates, and limited available ambient measurements make it difficult to establish the significance of a mechanism that has its dominant effect under preindustrial conditions. Our simulations predict more particle formation in the Amazon than is observed. However, the first observation of pure organic nucleation has now been reported for the free troposphere. Given the potentially significant effect on anthropogenic forcing, effort should be made to better understand such naturally driven aerosol processes.

Additional Information

© 2016 National Academy of Sciences. Edited by Joyce E. Penner, University of Michigan, Ann Arbor, MI, and accepted by Editorial Board Member A. R. Ravishankara August 20, 2016 (received for review February 19, 2016). Published online before print October 10, 2016, doi: 10.1073/pnas.1602360113 We thank P. Carrie, L.-P. De Menezes, J. Dumollard, F. Josa, I. Krasin, R. Kristic, A. Laassiri, O. S. Maksumov, B. Marichy, H. Martinati, S. V. Mizin, R. Sitals, A. Wasem, and M. Wilhelmsson for their important contributions to the experiment. We also thank D. Veber from Environment and Climate Change Canada for maintenance and calibrations of instruments at East Trout Lake and the Earth System Research Laboratory of the National Oceanic and Atmospheric Administration for collaboration with data collection and quality assurance and control software. We thank A. D. Clarke and C. L. S. Reddington for making available processed data from the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) campaign. We thank the European Organization for Nuclear Research (CERN) for supporting CLOUD with important technical and financial resources and providing a particle beam from the CERN Proton Synchrotron. The global modelling simulations were performed on Advanced Research Computing (ARC) high-performance computers at the University of Leeds. This research has received funding from the European Commission (EC) Seventh Framework and Horizon 2020 Programmes [Marie Curie Initial Training Network (MC-ITN) CLOUD-TRAIN Grant 316662, Marie Sklodowska-Curie Grants 656994 and 600377, European Research Council (ERC)-Consolidator Grant NANODYNAMITE 616075, and ERC-Advanced Grant ATMNUCLE 227463]; German Federal Ministry of Education and Research Project 01LK1222A; Swiss National Science Foundation Projects 200020_135307, 200021_140663, 206021_144947/1, and 20FI20_149002/1; Academy of Finland Center of Excellence Project 1118615; Academy of Finland Grants 135054, 133872, 251427, 139656, 139995, 137749, 141217, and 141451; the Finnish Funding Agency for Technology and Innovation; the Väisälä Foundation; the Nessling Foundation; Austrian Science Fund Project L593; Portuguese Foundation for Science and Technology Project CERN/FP/116387/2010; Swedish Research Council, Vetenskapsrådet Grant 2011-5120; Presidium of the Russian Academy of Sciences and Russian Foundation for Basic Research Grant 12-02-91522-CERN; United Kingdom Natural Environment Research Council Grant NE/K015966/1; the Royal Society (Wolfson Merit Award); National Science Foundation Grants AGS1136479, AGS1439551, AGS1447056, and CHE1012293; Caltech Environmental Science and Engineering Grant (Davidow Foundation); Dreyfus Award EP-11-117; the French National Research Agency; the Nord-Pas de Calais; and European Funds for Regional Economic Development Labex-Cappa Grant ANR-11-LABX-0005-01. Author contributions: H.G., K.S., J. Kirkby, A.O., U.B., M. Kulmala, J.C., and K.S.C. designed research; H.G., K.S., A.R., J.A., J. Kirkby, S.A.M., K.J.P., N.A.D.R., C.E.S., S. Sharma, and K.S.C. performed research; H.G., K.S., J. Duplissy, C. Frege, C.W., M.H., M. Simon, C.Y., J.A., J.T., T.N., I.K.O., R.W., E.M.D., A. Adamov, A. Amorim, A.-K.B., F.B., M.B., S.B., X.C., J.S.C., A.D., S.E., L.F., R.C.F., A.F., C. Fuchs, R.G., J.H., C.R.H., T.J., H.J., J. Kangasluoma, J. Kim, J. Kirkby, M. Krapf, A.K., A.L., K.L., V.M., S.M., U.M., O.P., F.P., T.P., A.P.P., K.J.P., M.P.R., L.R., N.S., S. Schobesberger, J.H.S., S. Sharma, M. Sipilä, G.S., Y.S., F.S., A.T., A.V., A.L.V., A.C.W., P.E.W., E.W., D.R.W., P.M.W., P.Y., X.Z., A.H., J. Dommen, N.M.D., D.R.W., U.B., M. Kulmala, J.C., and K.S.C. collected data; and H.G., J. Kirkby, N.M.D., and K.S.C. wrote the paper. The authors declare no conflict of interest. This article is a PNAS Direct Submission. J.E.P. is a Guest Editor invited by the Editorial Board. This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1602360113/-/DCSupplemental.

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Published - PNAS-2016-Gordon-12053-8.pdf

Supplemental Material - pnas.1602360113.sapp.pdf


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