The transport sector is one of the largest contributors to emissions worldwide and a key driver of air pollution in cities. Extensive research has been conducted to estimate the total emissions from the transport sector in urban areas. Nonetheless, much less attention has been paid to computational models to estimate emissions from public transport systems, where governmental policies can play a more direct role in promoting a transition to low-carbon mobility. This paper introduces the gtfs2emis model, a bottom-up method available as an R package to estimate tailpipe emissions of public transport systems at the vehicle level at high spatial and temporal resolutions. The method uses General Transit Feed Specification (GTFS) data, a standard format for public transport data widely adopted worldwide, which makes the method easily applicable to cities with limited data. The gtfs2emis model requires a GTFS feed of a given transport system and a table with general characteristics of the public transport fleet profile. The package can estimate over 16 pollutants and energy consumption based on emission factor models from Europe, the United States, and Brazil. It also includes functions to help users examine how tailpipe emissions are distributed across space, at different times of the day, and by types of vehicles. This paper presents a reproducible example of the city of São Paulo (Brazil) to demonstrate the gtfs2emis package and to discuss the potential applications and limitations of the proposed model.