Evolution of Vehicle Emission Factors in a Megacity Affected by Extensive Biofuel Use: Results of Tunnel Measurements in São Paulo, Brazil

Since 2001, four emission measurement campaigns have been conducted in multiple traffic tunnels in the megacity of São Paulo, Brazil, an area with a fleet of more than 7 million vehicles running on fuels with high biofuel contents: gasoline + ethanol for light-duty vehicles (LDVs) and diesel + biod...

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Bibliographic Details
Published inEnvironmental science & technology Vol. 55; no. 10; pp. 6677 - 6687
Main Authors Nogueira, Thiago, Kamigauti, Leonardo Yoshiaki, Pereira, Guilherme Martins, Gavidia-Calderón, Mario E, Ibarra-Espinosa, Sergio, Oliveira, Guilherme Librete de, Miranda, Regina Maura de, Vasconcellos, Pérola de Castro, Freitas, Edmilson Dias de, Andrade, Maria de Fatima
Format Journal Article
LanguageEnglish
Published American Chemical Society 18.05.2021
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Summary:Since 2001, four emission measurement campaigns have been conducted in multiple traffic tunnels in the megacity of São Paulo, Brazil, an area with a fleet of more than 7 million vehicles running on fuels with high biofuel contents: gasoline + ethanol for light-duty vehicles (LDVs) and diesel + biodiesel for heavy-duty vehicles (HDVs). Emission factors for LDVs and HDVs were calculated using a carbon balance method, the pollutants considered including nitrogen oxides (NO x ), carbon monoxide (CO), and sulfur dioxide, as well as carbon dioxide and ethanol. From 2001 to 2018, fleet-average emission factors for LDVs and HDVs, respectively, were found to decrease by 4.9 and 5.1% per year for CO and by 5.5 and 4.2% per year for NO x . These reductions demonstrate that regulations for vehicle emissions adopted in Brazil in the last 30 years improved air quality in the megacity of São Paulo significantly, albeit with a clear delay. These findings, especially those for CO, indicate that official emission inventories underestimate vehicle emissions. Here, we demonstrated that the adoption of emission factors calculated under real-world conditions can dramatically improve air quality modeling in the region.
ISSN:0013-936X
1520-5851
DOI:10.1021/acs.est.1c01006