TrackATruck heavy-duty truck emission inventory database is available now

2021-01-22 | Huan Liu

The TrackATruck heavy-duty truck emission inventory database developed by Huan Liu’s research group at the School of Environment of Tsinghua University has been launched recently. Traditional vehicle emission inventories are often calculated based on the statistics of truck registrations collected by local governments. However, because freight vehicles are different from other pollution sources, the vehicles are highly mobile, have a large range of activities, and the distribution of registrations and the distribution of actual driving areas do not overlap. Therefore, methods based on the distribution of registrations often lead to larger emissions deviations. TrackATruck aims to solve the problem of the accuracy of high-resolution emission data caused by the cross-regional transportation behavior of heavy-duty trucks. It is independently developed by Huan Liu’s research team. The new method reconstructs the transportation trajectory by tracking each heavy-duty truck with a weight of 12 tons or more and uses the emission algorithm coupled with two-level mapping to establish a bottom-up emission inventory. The bottom-level data of the emission inventory is the short-term trajectory of 9 billion heavy-duty trucks in the Beijing-Tianjin-Hebei region. The trajectory data of trucks comes from the national road freight vehicle public supervision and service platform.

Heavy duty truck emissions in the Jing-Jin-Ji region

The TrackATruck method can be used to improve the inventory used in regional air quality models while supporting research on the adjustment of China’s transportation structure and the realization of carbon neutrality vision. At present, the data of the Beijing-Tianjin-Hebei region is available with a grid resolution of 0.01°×0.01°, covering 7 types of species including NOx, PM2.5, PM10, TSP, HC, CO, and CO2. The download and use of the data must be marked with citations, and the cited documents are as follows. For other regions or times, please contact Huan Liu at Welcome to download and use the SEIM database through the new version of the MEIC website (


Liu, H.* et al. A big data approach to improving the vehicle emission inventory in China. Nature Communications 11, 2801, doi:10.1038/s41467-020-16579-w (2020).

Liu, H.* et al. Source–Receptor Relationship Revealed by the Halted Traffic and Aggravated Haze in Beijing during the COVID-19 Lockdown. Environmental Science & Technology, doi:10.1021/acs.est.0c04941 (2020).

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