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Sulfate and secondary organic aerosol (cloud aqSOA) can be chemically formed in cloud water. Model implementation of these processes represents a computational burden due to the large number of microphysical and chemical parameters. Chemical mechanisms have been condensed by reducing the number of chemical parameters. Here an alternative is presented to reduce the number of microphysical parameters (number of cloud droplet size classes). In-cloud mass formation is surface and volume dependent due to surface-limited oxidant uptake and/or size-dependent pH. Box and parcel model simulations show that using the effective cloud droplet diameter (proportional to total volume-to-surface ratio) reproduces sulfate and aqSOA formation rates within <= 30% as compared to full droplet distributions; other single diameters lead to much greater deviations. This single-class approach reduces computing time significantly and can be included in models when total liquid water content and effective diameter are available.

Plain Language Summary Chemical processes in cloud water modify chemical composition and size of airborne particles that scatter or absorb light and, thus, contribute to cooling or warming of our atmosphere. Describing clouds in global models is challenging since cloud properties are often not well constrained, and clouds are smaller than model grid boxes used to numerically describe atmospheric processes. The description of chemistry in clouds is a particular computational challenge since many, both chemical (concentrations of chemical species) and microphysical (e.g., cloud droplet sizes), parameters have to be considered. While previous studies attempted to solve this problem by reducing the number of chemical parameters by combining/omitting chemical processes and/or species, we take another route by reducing the number of microphysical parameters: Previous studies suggested cloud droplet size being important to predict in-cloud formation of inorganic (sulfate) and organic particle mass. However, details on drop sizes are usually not available from measurements or models. We find that the single "effective cloud droplet diameter," proportional to the total volume-to-surface area ratio of cloud droplets, reproduces in-cloud aerosol formation as compared to a full drop size distribution. This microphysical parameterization reduces computation time by a factor of similar to 20 and is suitable to improve prediction of chemical in-cloud mass formation in large-scale models.