A mobile platform for characterizing on-road tailpipe emissions and toxicity of ultrafine particles under real driving Conditions

Air Pollutants 01 natural sciences Motor Vehicles 13. Climate action Air Pollution 11. Sustainability Humans Particulate Matter Particle Size Gasoline Environmental Monitoring Vehicle Emissions 0105 earth and related environmental sciences
DOI: 10.1016/j.envres.2022.114523 Publication Date: 2022-10-18T16:06:11Z
ABSTRACT
Acute exposure to fresh traffic-related air pollutants (TRAPs) can be high for road users, including motorbike drivers, cyclists, and pedestrians. However, evaluating the toxicity of fresh traffic emissions from on-road vehicles is challenging since pollution properties can change dynamically within a short distance and time. This study demonstrated a mobile platform equipped with an On-Board Diagnostic II (OBDII) system, a tailor-made portable emission measurement system, and an electrostatic air-liquid interface exposure system with human monocytic THP-1 cells to characterize on-road tailpipe emissions under real driving conditions. High number concentrations up to 106-107 # cm-3 of ultrafine particles (UFPs) were observed for a gasoline engine at the cold-start stage and a diesel engine during particulate filter regeneration. In particular, a substantial fraction of freshly emitted UFPs within the size less than 23 nm were observed and should be cautioned. The potential toxicity of fresh TRAPs was quantified by cell viability, cytotoxicity, oxidative stress, and inflammatory biomarkers. Results show that the decreased cell viability, increased lactate dehydrogenase (LDH) activity, and high oxidative stress induced by the fresh TRAPs were potentially contributed by gaseous pollutants as well as particles, especially driving with the high idling frequency. Moreover, the dominant contributor to the toxicity is different for gasoline's and diesel's TRAPs. Characterizing on-road air pollutant toxicity as well as physicochemical properties using an innovative mobile platform can fill this knowledge gap.
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