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[Display omitted] As an important vehicle activity recognition method, vehicle specific power (VSP) has been widely used for on-road traffic emission modelling since its introduction in 1999. The conventional VSP (VSP_veh) is calculated from externally observable variables (EOVs) on the vehicle level and represents the power that a running vehicle needs to overcome. However, for hybrid electric vehicles (HEVs) with two power sources, vehicle activity is not always directly related to engine emissions. This study introduces the engine level VSP (VSP_eng), which estimates engine power from internally observable variables (IOVs) obtained from the vehicle's on-board electronic control unit (ECU). An engine bench test is first implemented to validate the estimation algorithm for VSP_eng. A real-world driving emission (RDE) test is then conducted with a HEV in Ningbo city of China to evaluate the performance of VSP_veh and VSP_eng in emission estimation. The results show a strong correlation between emission and VSP_eng (R2 = 0.9783), while a much weaker correlation was found between emission and VSP_veh (R2 = 0.4216). Further analysis indicates that this strong correlation between emission and VSP_eng applies to all driving conditions (urban, rural and highway). The differences between VSP_veh and VSP_eng are then highlighted by a combined correlation analysis where the four work modes of HEV can be graphically identified. Lastly, this study discusses the feasibility and potential benefits of the intelligent and remote vehicle emissions monitoring through the upcoming vehicle to everything (V2X) network. [ABSTRACT FROM AUTHOR]

A comprehensive year-round field campaign was conducted in the coastal city of Ningbo, China to examine the driving factors of oxidative potential (OP) of PM 2.5 and hence its potential health impacts. Using dithiothreitol (DTT) cell-free assay, OP of water-soluble (OPws) and methanol-soluble components (OPmeth) of PM 2.5 -based samples were measured. Volume-normalised OP (OP v ws and OP v meth) were higher in heating seasons, and mass-normalised OP (OP m ws and OP m meth) peaked in summer. Five sources were identified to be DTT active in OP v ws, with road dust (RD) being dominant, while four sources contributed to OP v meth, with industrial emission (IE) as the largest contributor. Water extracted more toxic components from RD while toxic components in IE and vehicle emission (VE) were more soluble in methanol. We further compared OP values between PM 2.5 of similar concentrations and observed that OP v ws prevailed in PM 2.5 toxicity during clean days (PM 2.5 concentration < 38.5 µg m−3), while OP v meth became dominant when PM 2.5 concentration was larger than 69.1 µg m−3, implying the need to extract whole PM 2.5 using both solvents to develop the mitigation strategy for reducing the overall PM 2.5 toxicity. Efforts should be devoted to controlling the emissions from dominant sources of both OP indicators in specific episode. [Display omitted] • Road dust dominated OP v ws, while industry and vehicle emissions governed OP v meth. • OP v ws and OP v meth prevailed PM 2.5 toxicity in respective clean and polluted days. • O 3 , selected metals and ions drove OP v ws under high Temp, RH and sun radiation. • OP v meth was affected by high-molecular-weight PAHs, Ni, Co, and Cl-. [ABSTRACT FROM AUTHOR]