Research interests
Theory and technology of dynamic traffic emission models for street, regional and global scales
Develop a multi-scale emission model based on traffic big data, dynamically obtained and updated the emission inventory model struct, including SLOVE, a dynamic simulation technology of urban road traffic emissions based on traffic flow, and established a regional freight emission simulation technology TrackATruck, a vehicle VOCs full-process emission model based on the analysis of the “drive-park-drive” chain behavior analysis, and the multi-scale ship emission inventory model SEIM, etc.
TrackATruck heavy freight vehicle emission inventory database download
SEIM database download
A multi-scale air quality coupling model adaptable for complex urban underlying surface environment
Propose a new method based on fluid mechanics calculations and machine learning to parameterize the internal wind field of the block canyon, which improved the ability to analyze the characteristics of vehicle pollution in the road micro-environment; Develop a method suitable for the complex urban underlying surface environment. The multi-scale air quality coupling model overcomes the problem that a single Euler model cannot simulate the rapid atmospheric evolution process of emissions. The spatial resolution of the near road simulation is increased from 1 km to 50 m, which fills the gaps in the multi-scale coupling model in China; A database of more than 150 species based on the refined emission process identifies the significant spatial heterogeneity of traffic source emissions in typical environments such as discharge outlets, near-sources, and homogeneous atmosphere.
Regional transportation emission control scheme and global emission reduction framework theory correlated to supply chain
Establish the coupling theory and technology of “driving force⟷traffic emissions⟷atmospheric environment⟷control plan”, explore and develop supply chain-related regional traffic control plan and global emission reduction framework theory; for international maritime trade, develop bilateral trade based on driver identification -Ship Emissions Coupling Model (TraSEIM) and Global Trade-Shipping Matrix Model (GTEMS), for the first time realizing the quantitative characterization of ship emissions and the driving force of trade, revealing the impact of climate change and population health of shipping, as well as global trade and man-made policies; for domestic freight trade, develop a regional freight model conversion model, and apply it evaluating the environmental effects of the “Freight Modal Shift” policy, and identify the evolution of the driving force of freight emissions over the years.