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African anthropogenic emissions inventory for gases and particles from 1990 to 2015

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dc.contributor.author Keita, Sekou
dc.contributor.author Liousse, Catherine
dc.contributor.author Assamoi, Eric-Michel
dc.contributor.author Thierno Doumbia
dc.contributor.author N’Datchoh, Evelyne Touré
dc.contributor.author Gnamien, Sylvain
dc.contributor.author Elguindi, Nellie
dc.contributor.author Granier, Claire
dc.contributor.author Yoboué, Véronique
dc.date.accessioned 2023-01-24T16:12:37Z
dc.date.available 2023-01-24T16:12:37Z
dc.date.issued 2021
dc.identifier.other https://doi.org/10.5194/essd-13-3691-2021
dc.identifier.uri http://197.159.135.214/jspui/handle/123456789/683
dc.description Research Article en_US
dc.description.abstract There are very few African regional inventories providing biofuel and fossil fuel emissions. Within the framework of the DACCIWA project, we have developed an African regional anthropogenic emission inventory including the main African polluting sources (wood and charcoal burning, charcoal making, trucks, cars, buses and two-wheeled vehicles, open waste burning, and flaring). To this end, a database on fuel consumption and emission factors specific to Africa was established using the most recent measurements. New spatial proxies (road network, power plant geographical coordinates) were used to convert national emissions into gridded inventories at a 0.1 0.1 spatial resolution. This inventory includes carbonaceous particles (black and organic carbon) and gaseous species (CO, NOx , SO2 and NMVOCs) for the period 1990–2015 with a yearly temporal resolution. We show that all pollutant emissions are globally increasing in Africa during the period 1990–2015 with a growth rate of 95 %, 86 %, 113 %, 112 %, 97% and 130% for BC, OC, NOx , CO, SO2 and NMVOCs, respectively. We also show that Western Africa is the highest emitting region of BC, OC, CO and NMVOCs, followed by Eastern Africa, largely due to domestic fire and traffic activities, while Southern Africa and Northern Africa are the highest emitting regions of SO2 and NOx due to industrial and power plant sources. Emissions from this inventory are compared to other regional and global inventories, and the emissions uncertainties are quantified by a Monte Carlo simulation. Finally, this inventory highlights key pollutant emission sectors in which mitigation scenarios should focus on. The DACCIWA inventory (https://doi.org/10.25326/56, Keita et al., 2020) including the annual gridded emission inventory for Africa for the period 1990–2015 is distributed by the Emissions of atmospheric Compounds and Compilation of Ancillary Data (ECCAD) system (https://eccad.aeris-data.fr/, last access: 19 July 2021). For review purposes, ECCAD has set up an anonymous repository where subsets of the DACCIWA data can be accessed directly through https://www7.obs-mip.fr/eccad/essd-surf-emis-dacciwa/ (last access: 19 July 2021). en_US
dc.language.iso en en_US
dc.publisher Earth Syst. Sci. Data, en_US
dc.title African anthropogenic emissions inventory for gases and particles from 1990 to 2015 en_US
dc.type Article en_US


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