A Kinetic Modeling Framework for Sulfuric Acid-Water Nucleation under Stratospheric Aerosol Injection Conditions

PI: Jinghao Zhai
Co-investigator: Mingyi Wang
Project team: Bingqing Zhang (Postdoctoral Scholar, Geophysical Sciences), Duzitian Li, (PhD Student, Geophysical Sciences)

Stratospheric aerosol injection (SAI) using sulfuric acid aerosols has been proposed as a potential climate intervention strategy to mitigate global warming by increasing the Earth’s reflectivity (albedo). To understand how SAI would work in practice, scientists need to accurately simulate the size distribution of the injected aerosols. This depends on an accurate estimation of nucleation rate, which describes how quickly new sulfuric acid–water particles form.

However, most existing estimates of nucleation rates are based on observations and laboratory experiments in the lower atmosphere (the troposphere), where sulfuric acid concentrations are much lower than those expected under SAI (in the stratosphere). Extending these observed relationships to the much higher concentrations relevant to SAI introduces substantial uncertainty in predictions of aerosol formation and their effect on climate.

This project will use a physically based kinetic framework to directly link sulfuric acid concentrations with nucleation rates, strengthening the scientific foundation for modeling stratospheric aerosols. Specifically, the team will:

• Use a kinetic model to simulate molecular-scale reaction pathways and the thermodynamics of small particle clusters, drawing on experimental data from the CERN CLOUD project to capture how particle formation shifts between different physical regimes; and
• Apply this model to predict nucleation rates under the temperatures, humidity levels, and sulfuric acid concentrations expected for SAI.

This project will create a more reliable way to predict how quickly new particles would form under different SAI conditions, reducing key uncertainties about how effectively they would reflect sunlight.