Poster's note: old, but new here.
http://ceepr.mit.edu/publications/working-papers/732

A Multi-control Climate Policy Process for a Designated Decision Maker
Henri F. Drake, Ronald L. Rivest, Alan Edelman, and John Deutch
July 2020

Persistent greenhouse gas (GHG) emissions threaten global climate goals and
have prompted consideration of climate controls supplementary to emissions
mitigation. We present an idealized model of optimally-controlled climate
change, which is complementary to simpler analytical models and more
comprehensive Integrated Assessment Models. We show that the four methods
of controlling climate damage– mitigation, carbon dioxide removal,
adaptation, and solar radiation modification– are not interchangeable, as
they enter at different stages of the causal chain that connects GHG
emissions to climate damages. Early and aggressive mitigation is always
necessary to stabilize GHG concentrations at a tolerable level. The most
cost-effective way of keeping warming below 2°C is a combination of all
four controls; omitting solar radiation modification– a particularly
contentious climate control– increases net control costs by 31%. At low
discount rates, near-term mitigation and carbon dioxide removal are used to
permanently reduce the warming effect
of GHGs. At high discount rates, however, GHGs concentrations increase
rapidly and future generations are required to use solar radiation
modification to offset a large greenhouse effect. We propose a policy
response process wherein climate policy decision-makers re-adjust their
policy prescriptions over time based on evolving climate outcomes and
revised model assumptions. We demonstrate the utility of the process by
applying it to three hypothetical scenarios in which model biases in 1)
baseline emissions, 2) geoengineering (CDR and SRM) costs, and 3) climate
feedbacks are revealed over time and control policies are re-adjusted
accordingly.

*For those interested, the MARGO model is built on the powerful Julia
programming
language that is open access and easy for interested persons to explore
different functional relationships and parameter values. It is available at:

https://github.com/hdrake/ClimateMARGO.jl

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