Abstract
The distribution pattern of near-road air pollutants is important for addressing air pollution issues. In this study, size-segregated particle number concentration (PNC) and black carbon (BC) concentration were measured at different locations perpendicular to a major roadway in Shanghai, aiming to improve the understanding of distribution patterns of traffic-related air pollutants. Results suggest that, despite the high emission level of on-road traffic, PNC 0.3-1 (particle diameter in 0.3–1 μm) exhibited negligible concentration gradients (no variation trend) with increasing distance from the road. BC and PNC >1 (>1 μm, coarse particles) exhibited significant spatial gradients, showing a pronounced increase in concentration near the road. This is closely associated with the high spatial homogeneity of fine particles and the high spatial variability of BC and coarse particles. The influence zone of traffic on pollutants was increased in rush hours due to increased emission intensity and pollutants dispersed a longer distance downwind. Additionally, the horizontal profiles of pollutants can all be well characterized by exponential curves, despite the small spatial gradient of PNC 0.3-1 . The concentration gradient and fall-off range of pollutants increased with the particle size (in 0.3–25 μm). This study provides implications that fine particles (e.g., PNC 0.1-1 , PM 1 ) are poor tracers of traffic emissions, which could perform poorly in characterizing the behavior of traffic emissions in the road environment but are more related to regional and background components. Moreover, the evaluation of pollutant traceability before the field study could contribute to improved experimental efficiency and more satisfactory results. • Near-road PNC 0.3-1 showed negligible spatial gradients (poor tracer of traffic emissions). • PNC 0.3-1 suggested pronounced temporal variability. • Black carbon and PNC >1 showed high spatial variability. • Pollutant decay distance increased in rush hours. • Near-road pollutant profiles can be well described by exponential curves.
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