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Evaluating city road dust emission characteristics with a dynamic method: A case study in Luoyang, China
Jiawei Chen1, Hanyang Man2, Wenying Cai1
1College of Environmental and Resource Sciences, Fujian Key Laboratory of Pollution Control & Resource Reuse, Fujian Normal University, Fuzhou 350007, China.
None:
Road dust, a significant contributor to non-exhaust particulate matter emissions in urban transport, poses considerable health risks, necessitating accurate and high-resolution data for effective control. The traditional AP-42 method offers data on point-specific dust emissions, while vehicle-based testing ascertains the relative emission intensity in the road network. However, a clear mathematical relationship between these measurements has been elusive, limiting efficiency in emission control. By integrating the On-board Conventional Pollutant Monitoring System with the AP-42 method, we devised a dynamic link between the concentration of particles in vehicle plumes and actual road dust emissions. This relationship is substantiated by a notable correlation (R2 = 0.91) between our emission factors and those calculated using the AP-42 method. Significant variations emerged in dust emission factors across road types, with changes between -30.1 % to +57.79 % from the average (0.05 g·vehicle-1·km-1), in tandem with traffic flow fluctuations of approximately ±90 %. Meteorological factors, except for continuous rainfall, showed minimal impact on dust emissions. However, our findings revealed a significant underestimation (58.87 %) of road dust PM10 emissions by the AP-42 method. Intriguingly, we found that short-range emission hotspots substantially contribute to total emissions, suggesting a potential 50 % reduction by controlling merely 8.8 % ± 2.5 % of the total road length. Our research elucidates the interplay between road dust emissions, road types, and human activities. The application of a dynamic, high-resolution assessment method enhances our understanding of the impacts of road dust on urban particulate pollution, allows accurate hotspot identification, and aids in developing efficacious strategies for air quality enhancement.

