Mobile source emissions have become a major contributor to air pollution in urban areas. Most of the previous studies focus on the emissions from a single source such as on-road mobile source (vehicles) or non-road mobile source (construction machinery, agricultural machinery, ships, railway diesel locomotives, aircraft), but few studies investigate the mobile source emissions as a whole. In this study, we introduced a method for developing mobile source emission inventory with high spatiotemporal resolution, and applied this method in Tianjin in 2017 to analyze the emission compositions and spatiotemporal characteristics there. The results showed that the CO, VOCs, NOx, and PM10 emissions from the mobile sources were 183.03, 64.18, 149.85, and 8.36 thousand tons, respectively. The on-road mobile source was the main contributor to CO and VOCs emissions, accounting for 85.38% and 86.60%, respectively. The non-road mobile source was the main contributor to NOx and PM10 emissions, accounting for 57.32% and 66.95%, respectively. According to the temporal distributions, the mobile source emissions were lowest in February for all pollutants. Moreover, they were highest in October for CO and VOCs and in August for NOx and PM10. Holidays (such as Spring Festival and National Day) have a significant impact on the temporal distribution of the mobile source emissions. According to the spatial distributions, the CO and VOCs emissions were concentrated in urban areas and roads with heavy traffic flow (highways and national highways), and the NOx and PM10 were concentrated in urban areas and port areas. The spatial distributions of different pollutants were determined by the location of their major contributors. This study can provide the required data for fine air pollution control and air quality simulation in Tianjin. Moreover, this method can be applied to the other areas where a mobile source emission inventory needs to be developed.
Keywords: Tianjin; emission factor; emission inventory; mobile source; spatial distribution.