https://dash.harvard.edu/handle/1/37375743

Author
Sun, Hongwei

*2023*

Citation
Sun, Hongwei. 2023. Modeling Aerosol Transport for Stratospheric Solar
Geoengineering: from Particle to Plume Scale. Doctoral dissertation,
Harvard University Graduate School of Arts and Sciences.
AbstractStratospheric Aerosol Injection (SAI) aims to offset some climate
hazards by releasing aerosols into the stratosphere to reflect solar
radiation. In this thesis, we outline the use of new modeling methods to
simulate aerosol transport in the stratosphere for SAI from particle scale
(Lagrangian trajectory model) to plume scale (plume-in-grid model).

We use a Lagrangian trajectory model driven by reanalyzed stratospheric
winds and modified to include sedimentation to model the transport of each
injected particle (from SAI) in the stratosphere and quantify the
sensitivity of particle lifetime to injection locations. From the physical
perspective, we analyze how background circulations influence particle
transport and lifetime in the stratosphere by considering Brewer-Dobson
Circulation, Quasi-Biennial Oscillation, tropopause height, poleward winds,
etc. From the engineering perspective, we explore various SAI injection
strategies to increase particle lifetime in the stratosphere. For example,
we find that an optimal choice of injection locations can increase particle
lifetime by 44% at 20 km, compared to without choosing injection locations.

SAI would almost certainly use aircraft for deployment, and these aircraft
would produce line-shaped plumes with strong concentration gradients, which
are hard for the global Eulerian model to resolve. To help global Eulerian
models resolve subgrid plumes in the stratosphere, a Lagrangian plume
model, comprising a Lagrangian trajectory model and an adaptive-grid plume
model with a sequence of plume cross-section representations (from a highly
resolved 2-D grid to a simplified 1-D grid based on a tradeoff between the
accuracy and computational cost), is created and embedded into a global
Eulerian model (i.e., GEOS-Chem model) to establish a multiscale
Plume-in-Grid (PiG) model. We compare this PiG model (with plume model) to
the GEOS-Chem model (without plume model) based on a 1-month simulation of
continuous inert tracer emissions by aircraft in the stratosphere in
several aspects including trace concentration, trace mixing (entropy),
nonlinear processes, and computing efficiency. For example, with the plume
model, the final injected tracer is more concentrated and approximately 1/3
of the tracer is at concentrations 2-4 orders of magnitude larger compared
to without the plume model.
*Source: Digital Access to Scholarship at Harvard*

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