Is there an aerosol signature of chemical cloud processing?
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Is there an aerosol signature of chemical cloud processing?
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    Atmospheric Chemistry and Physics, 18(21), 16099-16119.
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  • Description:
    The formation of sulfate and secondary organic aerosol mass in the aqueous phase (aqSOA) of cloud and fog droplets can significantly contribute to ambient aerosol mass. While tracer compounds give evidence that aqueousphase processing occurred, they do not reveal the extent to which particle properties have been modified in terms of mass, chemical composition, hygroscopicity, and oxidation state. We analyze data from several field experiments and model studies for six air mass types (urban, biogenic, marine, wild fire biomass burning, agricultural biomass burning, and background air) using aerosol size and composition measurements for particles 13-850 nm in diameter. We focus on the trends of changes in mass, hygroscopicity parameter K, and oxygen-to-carbon (O / C) ratio due to chemical cloud processing. We find that the modification of these parameters upon cloud processing is most evident in urban, marine, and biogenic air masses, i.e., air masses that are more polluted than very clean air (background air) but cleaner than heavily polluted plumes as encountered during biomass burning. Based on these trends, we suggest that the mass ratio (R-tot) of the potential aerosol sulfate and aqSOA mass to the initial aerosol mass can be used to predict whether chemical cloud processing will be detectable. Scenarios in which this ratio exceeds R-tot similar to 0.5 are the most likely ones in which clouds can significantly change aerosol parameters. It should be noted that the absolute value of R-tot depends on the considered size range of particles. R-tot is dominated by the addition of sulfate (R-sulf) in all scenarios due to the more efficient conversion of SO2 to sulfate compared to aqSOA formation from organic gases. As the formation processes of aqSOA are still poorly understood, the estimate of R-aqSOA is likely associated with large uncertainties. Comparison to R-tot values as calculated for ambient data at different locations validates the applicability of the concept to predict a chemical cloud-processing signature in selected air masses.
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