Multispecies and high-spatiotemporal-resolution database of vehicular emissions in Brazil

Autor: L. Hoinaski, T. V. Vasques, C. B. Ribeiro, B. Meotti
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Earth System Science Data, Vol 14, Pp 2939-2949 (2022)
Druh dokumentu: article
ISSN: 1866-3508
1866-3516
DOI: 10.5194/essd-14-2939-2022
Popis: In this article, we present the BRAzilian Vehicular Emissions inventory Software (BRAVES) database, a multispecies and high-spatiotemporal-resolution database of vehicular emissions in Brazil. We provide this database using spatial disaggregation based on road density, temporal disaggregation using vehicular flow profiles, and chemical speciation based on local studies and the SPECIATE 5.1 database from the United States Environmental Protection Agency (US EPA). Our BRAVES database provides hourly and annual emissions of 41 gaseous and particle pollutants, where users can define the spatial resolution, which ranges from a coarse to a very refined scale. Spatial correlation analysis reveals that the BRAVES database reaches better performance than the vehicular emissions inventory from the Emissions Database for Global Atmospheric Research (EDGAR). A comparison with the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) surface concentration confirms the consistency and reliability of the BRAVES database in representing the spatial pattern of vehicular emissions. Compared to EDGAR, the BRAVES database brings more spatial, temporal, and chemical details. These additional features are crucial to understanding important atmospheric chemistry processes in Brazil. All codes and inputs are freely available, and the outputs are compatible with the input requirements of sophisticated chemical transport models. We envision that our database will enable the scientific and environmental community to gain new insights into vehicular emissions and their effects in Brazil, where emissions inventories are scarce and urgently needed. The BRAVES database is freely available at https://doi.org/10.5281/zenodo.6588692 (Hoinaski et al., 2022).
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