Abstract

Abstract. Mineral dust is the largest source of aerosol iron (Fe) to the offshore global ocean, but acidic processing of coal fly ash (CFA) in the atmosphere could be an important source of soluble aerosol Fe. Here, we determined the Fe speciation and dissolution kinetics of CFA from Aberthaw (United Kingdom), Krakow (Poland), and Shandong (China) in solutions which simulate atmospheric acidic processing. In CFA PM10 fractions, 8 %–21.5 % of the total Fe was found to be hematite and goethite (dithionite-extracted Fe), and 2 %–6.5 % was found to be amorphous Fe (ascorbate-extracted Fe), while magnetite (oxalate-extracted Fe) varied from 3 %–22 %. The remaining 50 %–87 % of Fe was associated with other Fe-bearing phases, possibly aluminosilicates. High concentrations of ammonium sulfate ((NH4)2SO4), often found in wet aerosols, increased Fe solubility of CFA up to 7 times at low pH (2–3). The oxalate effect on the Fe dissolution rates at pH 2 varied considerably, depending on the samples, from no impact for Shandong ash to doubled dissolution for Krakow ash. However, this enhancement was suppressed in the presence of high concentrations of (NH4)2SO4. Dissolution of highly reactive (amorphous) Fe was insufficient to explain the high Fe solubility at low pH in CFA, and the modelled dissolution kinetics suggest that other Fe-bearing phases such as magnetite may also dissolve relatively rapidly under acidic conditions. Overall, Fe in CFA dissolved up to 7 times faster than in a Saharan dust precursor sample at pH 2. Based on these laboratory data, we developed a new scheme for the proton- and oxalate-promoted Fe dissolution of CFA, which was implemented into the global atmospheric chemical transport model IMPACT (Integrated Massively Parallel Atmospheric Chemical Transport). The revised model showed a better agreement with observations of Fe solubility in aerosol particles over the Bay of Bengal, due to the initial rapid release of Fe and the suppression of the oxalate-promoted dissolution at low pH. The improved model enabled us to predict sensitivity to a more dynamic range of pH changes, particularly between anthropogenic combustion and biomass burning aerosols.

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