Applying real-world driving emissions (RDE) data to machine learning, this study investigated vehicular emission characteristics and reduction strategies in Tianjin and Xining, two cities at different altitudes. Significant differences in CO₂ and particulate number (PN) emissions were observed, primarily due to altitude-induced changes in air pressure, affecting air resistance and combustion efficiency. Driving conditions and emission standards were identified as key factors influencing emissions, with road grade and air pressure playing crucial roles at high altitudes. Quantitative assessments showed that speed guidance reduced PN emissions by 34.8% in high-altitude areas, while emission standard upgrades consistently reduced CO₂ emissions by 6.1% across altitudes. These results underscore the need for tailored emission control policies that adapt to local environmental and altitude conditions.
Keywords: High altitude; Particulate number; Real driving emission; Vehicle emission modeling.
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