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Sulfate Formation Enhanced by a Cocktail of High NOx, SO2, Particulate Matter, and Droplet pH during Haze-Fog Events in Megacities in China: An Observation-Based Modeling Investigation

This paper was not found in any repository; the policy of its publisher is unknown or unclear.
This paper was not found in any repository; the policy of its publisher is unknown or unclear.

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Abstract

In recent years in a few Chinese megacities, fog events lasting one to a few days have been frequently associated with high levels of aerosol loading characterized by high sulfate (as high as 30 mu g m(-3)), therefore termed as haze-fog events. The concomitant pollution characteristics include high gas-phase mixing ratios of SO2 (up to 71 ppbv) and NO2 (up to 69 ppbv), high aqueous phase pH (5-6), and smaller fog droplets (as low as 2 mu m), resulting from intense emissions from fossil fuel combustion and construction activities supplying abundant Ca2+. In this work, we use an observation-based model for secondary inorganic aerosols (OBM-SIA) to Simulate sulfate formation pathways under conditions of haze-fog events encountered in Chinese megacities. The OBM analysis has identified, at a typical haze-fogwater pH of 5.6, the most important pathway to be oxidation of S-(IV) by dissolved NO2, followed by the heterogeneous reaction of SO2 on the aerosol surface. The aqueous phase oxidation of S-(IV) by H2O2 is a very minor formation pathway as a result of the high NOx conditions suppressing H2O2 formation. The model results indicate that the unique cocktail of high fogwater pH, high concentrations of NO2, SO2, and PM, and small fog droplets are capable of greatly enhancing sulfate formation. Such haze-fog conditions could lead to rapid sulfate production at night and subsequently high PM2.5 in the morning when the fog evaporates. Sulfate formation is simulated to be highly sensitive to fogwater pH, PM, and precursor gases NO2 and SO2. Such insights on major contributing factors imply that reduction of road dust and NOx emissions could lessen PM2.5 loadings in Chinese megacities during fog events.