Comment on "Reduced efficacy of marine cloud brightening geoengineering due to in-plume aerosol coagulation: parameterization and global implications" by Stuart et al. (2013)
Abstract. We examine the parameterized model of Stuart et al. (2013) vis-à-vis a diffusion-based model proposed by us earlier (Anand and Mayya, 2011) to estimate the fraction of aerosol particles surviving coagulation in a dispersing plume. While the Stuart et al. approach is based on the solutions to the coagulation problem in an expanding plume model, the diffusion-based approach solves the diffusion–coagulation equation for a steady-state standing plume to arrive at the survival fraction correlations. We discuss the differences in the functional forms of the survival fraction expressions obtained in the two approaches and compare the results for the case studies presented in Stuart et al. (2013) involving different particle emission rates and atmospheric stability categories. There appears to be a better agreement between the two models at higher survival fractions as compared to lower survival fractions; on the whole, the two models agree with each other within a difference of 10%. The diffusion-based expression involves a single exponent fit to a theoretically generated similarity variable combining the parameters of the problem with inbuilt exponents and hence avoids the multi-exponent parameterization exercise. It also possesses a wider range of applicability in respect of the source and atmospheric parameters as compared to that based on parameterization. However, in the diffusion model, the choice of a representative value for the coagulation coefficient is more prescriptive than rigorous, which has been addressed in a more satisfactory manner by the parameterization method. The present comparative exercise, although limited in scope, confirms the importance of aerosol microphysical processes envisaged by Stuart et al. for cloud brightening applications. In a larger context, it seems to suggest that either of the two forms of expressions might be suitable for incorporation into global-/regional-scale air pollution models for predicting the contribution of localized sources to the particle number loading in the atmosphere.