Articles | Volume 11, issue 1
https://doi.org/10.5194/gmd-11-369-2018
https://doi.org/10.5194/gmd-11-369-2018
Model experiment description paper
 | 
29 Jan 2018
Model experiment description paper |  | 29 Jan 2018

Historical (1750–2014) anthropogenic emissions of reactive gases and aerosols from the Community Emissions Data System (CEDS)

Rachel M. Hoesly, Steven J. Smith, Leyang Feng, Zbigniew Klimont, Greet Janssens-Maenhout, Tyler Pitkanen, Jonathan J. Seibert, Linh Vu, Robert J. Andres, Ryan M. Bolt, Tami C. Bond, Laura Dawidowski, Nazar Kholod, June-ichi Kurokawa, Meng Li, Liang Liu, Zifeng Lu, Maria Cecilia P. Moura, Patrick R. O'Rourke, and Qiang Zhang

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Cited articles

Akagi, S. K., Yokelson, R. J., Wiedinmyer, C., Alvarado, M. J., Reid, J. S., Karl, T., Crounse, J. D., and Wennberg, P. O.: Emission factors for open and domestic biomass burning for use in atmospheric models, Atmos. Chem. Phys., 11, 4039–4072, https://doi.org/10.5194/acp-11-4039-2011, 2011.
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Amann, M., Klimont, Z., and Wagner, F.: Regional and global emissions of air pollutants: recent trends and future scenarios, Annu. Rev. Env. Resour., 38, 31–55, https://doi.org/10.1146/annurev-environ-052912-173303, 2013.
Amann, M., Bertok, I., Borken-Kleefeld, J., Cofala, J., Heyes, C., Hoglund-Isaksson, L., Kiesewetter, G., Klimont, Z., Schopp, W., Vellinga, N., and Winiwarter, W.: Adjusted historic emission data, projections, and optimized emission reduction targets for 2030 – a comparison with COM data 2013, IIASA, Laxenburg, Austria, available at: http://ec.europa.eu/environment/air/pdf/review/TSAP_16a.pdf (last access: 15 January 2018), 2015.
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Short summary
Historical emission trends are key inputs to Earth systems and atmospheric chemistry models. We present a new data set of historical (1750–2014) anthropogenic gases (CO, CH4, NH3, NOx, SO2, NMVOCs, BC, OC, and CO2) developed with the Community Emissions Data System (CEDS). This improves on existing inventories as it uses consistent methods and data across emissions species, has annual resolution for a longer and more recent time series, and is designed to be transparent and reproducible.