Emission characteristics and control scenario analysis of VOCs from heavy-duty diesel trucks.

Vehicle exhaust substantially contributes to ambient volatile organic compounds (VOCs) that imperil environmental and human health. The quantitative characterization of VOCs derived from heavy-duty diesel trucks (HDDTs) at a high spatiotemporal resolution is an important prerequisite of atmospheric quality management. However, there is little knowledge about VOC emission characteristics and accurate control policies of HDDTs owing to limited fine-grained traffic activity data. To fill this gap, this research aims to construct a link-level and hourly-based VOC emission inventory of HDDTs by combining fine-grained trajectory data, detailed vehicle specification information, localized emission factors, and underlying geographic information. The emission reduction potentials of different emission control scenarios were also evaluated. The research was conducted in Hebei Province, a predominant heavy industrial province in China. The results demonstrated that HDDTs with China 3 and below emission standards contributed to 74.85% of the HDDT generated VOC emissions, although they only accounted for 25.43% of the HDDTs operating on the road networks. The VOC emission characteristics of HDDTs were further explored at various temporal and spatial scales. Temporally, the difference between the maximum and minimum hourly VOC emissions reached 29.19%, and daily emission changes were considerably affected by holidays. Spatially, road segments with higher emission intensities and statistically significant emission hot spots were primarily distributed in intercity highways and national freeways, reflecting the contribution of high freight activity to the VOC emissions. Emission control scenario simulations demonstrated that improving HDDT emission standards can reduce VOC emissions by up to 80.06%. The results of this study contribute to a deeper understanding of the spatiotemporal patterns of VOC emissions from HDDTs and the effectiveness of emission reduction measures.