Increased contribution to PM_2.5 from traffic-influenced road dust in Shanghai over recent years and predictable...

Traffic contributes to fine particulate matter (PM_2.5) in the atmosphere through engine exhaust emissions and road dust generation. However, the evolution of traffic related PM_2.5 emission over recent years remains unclear, especially when various efforts to reduce emission e.g., aftertreatment technologies and high emission standards from China IV to China V, have been implemented. In this study, hourly elemental carbon (EC), a marker of primary engine exhaust emissions, and trace element of calcium (Ca), a marker of road dust, were measured at a nearby highway sampling site in Shanghai from 2016 to 2019. A random forest-based machine learning algorithm was applied to decouple the influences of meteorological variables on the measured EC and Ca, revealing the deweathered trend in exhaust emissions and road dust. After meteorological normalization, we showed that non-exhaust emissions, i.e., road dust from traffic, increased their fractional contribution to PM_2.5 over recent years. In particular, road dust was found to be more important, as revealed by the deweathered trend of Ca fraction in PM_2.5, increasing at 6.1% year^-1, more than twice that of EC (2.9% year^-1). This study suggests that while various efforts have been successful in reducing vehicular exhaust emissions, road dust will not abate at a similar rate. The results of this study provide insights into the trend of traffic-related emissions over recent years based on high temporal resolution monitoring data, with important implications for policymaking.