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Published April 10, 2012 | Published
Journal Article Open

Climatic effects of 1950-2050 changes in US anthropogenic aerosols - Part 1: Aerosol trends and radiative forcing


We calculate decadal aerosol direct and indirect (warm cloud) radiative forcings from US anthropogenic sources over the 1950–2050 period. Past and future aerosol distributions are constructed using GEOS-Chem and historical emission inventories and future projections from the IPCC A1B scenario. Aerosol simulations are evaluated with observed spatial distributions and 1980–2010 trends of aerosol concentrations and wet deposition in the contiguous US. Direct and indirect radiative forcing is calculated using the GISS general circulation model and monthly mean aerosol distributions from GEOS-Chem. The radiative forcing from US anthropogenic aerosols is strongly localized over the eastern US. We find that its magnitude peaked in 1970–1990, with values over the eastern US (east of 100° W) of −2.0 W m⁻² for direct forcing including contributions from sulfate (−2.0 W m⁻²), nitrate (−0.2 W m⁻²), organic carbon (−0.2 W m⁻²), and black carbon (+0.4 W m⁻²). The uncertainties in radiative forcing due to aerosol radiative properties are estimated to be about 50%. The aerosol indirect effect is estimated to be of comparable magnitude to the direct forcing. We find that the magnitude of the forcing declined sharply from 1990 to 2010 (by 0.8 W m⁻² direct and 1.0 W m⁻² indirect), mainly reflecting decreases in SO₂ emissions, and project that it will continue declining post-2010 but at a much slower rate since US SO2 emissions have already declined by almost 60% from their peak. This suggests that much of the warming effect of reducing US anthropogenic aerosol sources has already been realized. The small positive radiative forcing from US BC emissions (+0.3 W m⁻² over the eastern US in 2010; 5% of the global forcing from anthropogenic BC emissions worldwide) suggests that a US emission control strategy focused on BC would have only limited climate benefit.

Additional Information

© Author(s) 2012. This work is distributed under the Creative Commons Attribution 3.0 License. Received: 20 May 2011 – Discussion started: 29 Aug 2011 – Revised: 21 Mar 2012 – Accepted: 29 Mar 2012 – Published: 10 Apr 2012. This work was supported by the Electric Power Research Institute (EPRI) and an EPA Science to Achieve Results (STAR) Graduate Research Fellowship to Eric Leibensperger. The EPRI and EPA have not officially endorsed this publication and the views expressed herein may not reflect those of the EPRI and EPA. This work utilized resources and technical support offered by the Harvard University School of Engineering and Applied Science Instructional and Research Computing Services. We would like to thank Jack Yatteau for computational assistance. We thank the editor and two anonymous reviewers whose comments helped improve this work. Edited by: M. Kanakidou.

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