Abstract

Abstract. Reactive oxygen species (ROS), such as OH, HO2 and H2O2, affect the oxidation capacity of the atmosphere and cause adverse health effects of particulate matter. The role of transition metal ions (TMIs) in impacting the ROS concentrations and conversions in the atmospheric aqueous phase has been recognized for a long time. Model studies usually assume that the total TMI mass as measured in bulk aerosol or cloud water samples is distributed equally across all particles or droplets. This assumption is contrary to single-particle measurements that have shown that only a small number fraction of particles contain iron and other TMIs (FN,Fe<100 %), which implies that also not all cloud droplets contain TMIs. In the current study, we apply a box model with an explicit multiphase chemical mechanism to simulate ROS formation and cycling in aqueous aerosol particles and cloud droplets. Model simulations are performed for the range of 1 % ≤ FN,Fe ≤ 100 % for constant pH values of 3, 4.5 and 6 and constant total iron mass concentration (10 or 50 ng per cubic meter of air). Model results are compared for two sets of simulations with FN,Fe<100 % (FeN<100) and 100 % (FeBulk). We find the largest differences between model results in OH and HO2 / O2- concentrations at pH = 6. Under these conditions, HO2 is subsaturated in the aqueous phase because of its high effective Henry's law constant and the fast chemical loss reactions of the O2- radical anion. As the main reduction process of Fe(III) is its reaction with HO2 / O2-, we show that the HO2 subsaturation leads to Fe(II) / Fe(total) ratios for FN,Fe<100 % that are lower by a factor of ≤ 2 as compared to bulk model approaches. This trend is largely independent of the total iron concentration, as both chemical source and sink rates of HO2 / O2- scale with the iron concentration. We compare model-derived reactive uptake parameters γOH and γHO2 for the full range of FN,Fe. While γOH is not affected by the iron distribution, the calculated γHO2 values range from 0.0004 to 0.03 for FN,Fe = 1 % and 100 %, respectively. Implications of these findings are discussed for the application of lab-derived γHO2 in models to present reactive HO2 uptake on aerosols. We conclude that the iron distribution (FN,Fe) should be taken into account to estimate the ROS concentrations and oxidation potential of particulate matter that might be overestimated by bulk sampling and model approaches. Our study suggests that the number concentration of iron-containing particles FN,Fe may be more important than the total iron mass concentration in determining ROS budgets and uptake rates in cloud and aerosol water.

Highlights

  • The main oxidants in the atmospheric aqueous phases of cloud and aerosol particles include the hydroxyl radical (OH) and hydrogen peroxide (H2O2), whose concentration levels are closely linked to the hydroperoxy radical (HO2 / O−2 )

  • A similar size range for iron-containing particles but smaller average number fraction (∼ 4 %) was found above the English Channel in air masses affected by steel works (Choël et al, 2007). As particles in this size range commonly act as cloud condensation nuclei (CCN), these analyses suggest that not all cloud droplets contain iron and that the measured iron mass concentration in aerosol populations is not distributed among all particles

  • The role of transition metal ion (TMI) reactions for impacting oxidant levels (OH, HO2, H2O2) in the atmospheric aqueous phase has been recognized for a long time

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Summary

Introduction

The main oxidants in the atmospheric aqueous phases of cloud and aerosol particles include the hydroxyl radical (OH) and hydrogen peroxide (H2O2), whose concentration levels are closely linked to the hydroperoxy radical (HO2 / O−2 ) The concentrations of these reactive oxygen species (ROS) are influenced by various redox reactions of transition metal ions (TMIs). The oxidation of iron(II) by hydrogen peroxide (Fenton reaction) has been identified as one of the main chemical sources of the OH radical in cloud water (Ervens et al, 2003; Deguillaume et al, 2004; Tilgner et al, 2013), aqueous-phase aerosol particles (Al-Abadleh, 2015) and lung fluid (Charrier et al, 2015).

Model description
Dg 3 α
Model simulations
Cloud droplets
Aqueous aerosol particles
Partitioning coefficient
Comparison of bulk aqueous-phase concentrations
Enhanced H2O2 partitioning into aerosol water
Oxidation state of iron
Calculation of γOH and γHO2
Findings
Summary and conclusions
Full Text
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