A study by Ashan et al. (2023) in which FORCeS members Dirk Olivié, Leighton Regayre, and Michael Schulz participated, was just published in EGU Atmospheric Chemistry and Physics. This study delves into the ramifications of anthropogenic emissions of aerosols and precursor compounds on the Earth-atmosphere energy equilibrium, cloud formation, precipitation dynamics, and their consequential impact on human health and environmental integrity. By investigating 11 distinct climate and chemistry models, the research investigates the sensitivity of model outcomes to the following parameters: 1) the altitude of sulphur dioxide (SO2) injection, 2) the temporal variability of SO2 and black carbon (BC) particulate emissions, 3) the fraction of SO2 emissions that transforms into particulate phase sulphate (SO4).
A substantial variability in atmospheric lifetime across models for SO2, SO4, and BC was observed, with SO2 showing significant relative discrepancies. This variance highlights existing uncertainties in fundamental aspects of atmospheric sulphur chemistry. Among the perturbations studied, the elevation of SO2 injection emerged as having the most considerable overall impact, notably influencing global mean net radiative flux, SO2 lifespan over Northern Hemisphere landmasses, surface concentrations of SO2 (experiencing up to a 59% reduction), and surface sulphate concentrations (showing up to a 23% increase).
Specifically, altering the release altitude of SO2 resulted in increased SO2 and SO4 column burdens, alongside shortwave cooling effects of varying degrees. However, its effects on implied cloud forcing exhibited inconsistency across models in terms of the direction of change. In addition, the assumed fraction of SO4 emission exhibited a significant chain reaction on net radiative flux and surface sulphate concentration. The lack of standardization in these parameters across models underscores an overlooked source of inter-model diversity typically disregarded in model intercomparisons.
Consequently, these findings underscore the necessity of accurately and consistently representing anthropogenic emission injection altitudes and SO4 emission fractions within global models to enhance predictive precision and ensure more reliable projections.