Synergistic enhancement of urban haze by nitrate uptake into transported hygroscopic particles in the Asian continental outflow

Abstract

Haze pollution is affected by local air pollutants, regional transport of background particles and precursors, atmospheric chemistry related to secondary aerosol formation, and meteorological conditions conducive to physical, dynamical, and chemical processes. In the large, populated and industrialized areas like the Asian continental outflow region, the combination of regional transport and local stagnation often exacerbates urban haze pollution. However, the detailed chemical processes underlying the enhancement of urban haze induced by the combined effect of local emissions and transported remote pollutants are still unclear. Here, we demonstrate an important role of transported hygroscopic particles in increasing local inorganic aerosols, by studying the chemical composition of PM2.5 collected between October 2012 and June 2014 in Seoul, a South Korean megacity in the Asian continental outflow region, using the ISOR-ROPIA II thermodynamic model. PM2.5 measured under the condition of regional transport from the upwind source areas in China was higher in mass concentration and richer in secondary inorganic aerosol (SIA) species (SO42-, NO3, and NH4+) and aerosol liquid water (ALW) compared to that measured under non-transport conditions. The secondary inorganic species and ALW were both increased, particularly in cases with high PM2.5 levels, and this indicates inorganic species as a major driver of hygroscopicity. We conclude that the urban haze pollution in a continental outflow region like Seoul, particularly during the cold season, can be exacerbated by ALW in the transported particles, which enhances the nitrate partitioning into the particle phase in NOx- and NH3-rich urban areas. This study reveals the synergistic effect of remote and local sources on urban haze pollution in the downwind region and provides insight into the nonlinearity of domestic and foreign contributions to receptor PM2.5 concentrations in numerical air quality models.