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Updated: Jul 3, 2025

Measuring Sub-23 Nanometer Real Driving Particle Number Emissions Using the Portable DownToTen Sampling System
Published on: May 22, 2020
Exploring particle concentrations and inside-to-outside ratios in vehicles: A real-time road test study
Danlu Wang1, Zhenglei Li2, Yunjing Wang3
1State Environmental Protection Key Laboratory of Vehicle Emission Control and Simulation, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China.
Abstract:
In transportation microenvironments, humans exposed to particulate matter (PM) inside vehicles can experience higher levels of daily exposure. To make inside-vehicle PM exposure measurements more feasible and easy under real driving conditions, and to quantify the relationship between the concentrations and influencing factors, we assessed PM1, PM2.5, and PM10. levels. Additionally, we collected key influencing factors to develop predictive models. The measurements of PM1, PM2.5, and PM10 concentrations showed that the ventilation setting was a significant influencing factor. The concentrations decreased significantly under the recirculation setting (RC) compared to the outside air setting (OA). The inside-to-outside (I/O) ratios of PM were 1.69 to 1.93-fold higher than those of RC under OA conditions. However, a substantial reduction in the I/O ratios was observed when RC was employed. Although both the concentrations and I/O ratios exhibited significant differences, they demonstrated strong potential relationships. PM2.5 I/O ratios accounted for over 85 % of the variation in the PM1 and PM10 I/O ratios. The developed models for the I/O ratios of PM accounted for >40 and 60 % of the variation in the measured I/O ratios for RC and OA, respectively. We used the vehicle age, vehicle interior volume, speed, cabin temperature, cabin humidity, and their higher-order terms as predictive variables. It is important to note that the influential predictive feature importance differed under RC and OA, and considering the vehicle characteristics between vehicles of the same type may be necessary when using RC. Overall, these findings indicate that the inside-vehicle PM exposure can be measured more easily under real driving conditions by considering the key influencing factors and utilizing the developed predictive models.
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