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The effect of black carbon (BC) on air quality and the climate is still unclear, which is partly because of the poor understanding regarding the BC aging process in the atmosphere. In this work, we developed a new approach to simulate the BC mixing state (i.e., other species coated on the BC surface) based on an emissions inventory and back-trajectory analysis. The model tracks the evolution of the BC aging degree (characterized by the size ratio of the whole particle and BC core) during atmospheric transport. Using the models, we quantified the mass-averaged aging degree of total BC particles transported to a receptor (e.g., an observation site) from various emission origins (i.e., 0.25∘×0.25∘ grids). The simulations showed good agreement with the field measurements, which validated our model calculation. Modeling the aging process of BC during atmospheric transport showed that it was strongly dependent on emission levels. BC particles from extensive emission origins (i.e., polluted regions) were characterized by a higher aging degree during atmospheric transport due to more co-emitted coating precursors. On the other hand, high-emission regions also controlled the aging process of BC particles that were emitted from cleaner regions and passed through these polluted regions during atmospheric transport. The simulations identified the important roles of extensive emission regions in the BC aging process during atmospheric transport, implying the enhanced contributions of extensive emission regions to BC light absorption. This provides a new perspective on the phenomenon of pollution building up in the North China Plain, further demonstrating that this is mainly driven by regional transport and transformation. The simulation of the BC aging degree during atmospheric transport provided more clues for improving air pollution and climate change.
