A high-resolution emissions inventory and its spatiotemporal pattern variations for heavy-duty diesel trucks in Beijing, China

摘要: Abstract Heavy-duty diesel trucks (HDDTs) cause serious pollution, and a high spatiotemporal resolution emissions inventory is valuable assessment tool for use in quantitatively understanding the mechanisms of HDDTs scientifically developing associated reduction measures. This study aims to comprehensively utilize multi-source data on transportation—including fine-scale trajectories HDDTs, road traffic conditions, attribute networks HDDTs—supplemented by relatively mature vehicle pollution models establish Beijing using bottom-up approach. Spatial statistical techniques, including spatial autocorrelation, high/low clustering, outlier analysis, are also used explore distribution pattern city. The results showed following: (1) spatially, nitrogen oxide (NOx) particulate matter (PM) emission hotspots spread from sixth-ring roads fourth-ring daytime nighttime. segments with intensities have pronounced agglomeration effects at night, but these scattered during daytime. (2) Temporally, total HDDT NOx consistent volume trends lower major festivals. highest occur intercity highways, this reflects severe impact that freight has air quality. dominant vehicles belonging China 4 standard. (3) PM significant autocorrelation exhibit high-value clustering as whole. (4) At different time intervals, High-High/Low-Low outliers network pollutant intensity. High-Low mainly distributed within roads, number gradually reduces between night day. Low-High affected heterogeneous exhibits discontinuous characteristics. Our effectively evaluate Beijing’s control measures provide scientific decision-making basis targeted strategies HDDTs.