Abstract:
Achieving the temperature goals of the Paris Agreement will require 100 to 300 gigatons of carbon dioxide removal (CDR) this century. As such large-scale interventions become central to climate planning, distinguishing between temporary carbon fluxes and durable atmospheric removals is essential. Yet current CDR accounting frameworks often obscure core issues of permanence, additionality, and attribution, raising questions about what truly constitutes meaningful climate impact. This talk uses enhanced weathering (EW) as a case study to examine how mechanistic models can illuminate the underlying processes that govern carbon removal in soil-based CDR. I will highlight our recent modeling work at the soil–groundwater interface, including the development of “alkalinity tags” as a diagnostic tool to evaluate and improve existing proxy-based quantification methods. This example highlights both the diagnostic power of mechanistic models and the current limitations in data integration, parameterization, and model structure that restrict their fitness for regulatory or financial decision-making. The talk concludes by broadening to other soil-based CDR pathways and raising emerging questions around model governance: what constitutes “fit-for-purpose” modeling in carbon markets, and how should model-based evidence be evaluated when used to support claims of durable removal?
Bio:
Kate Maher is a Professor of Earth System Science at Stanford University and a Senior Fellow at the Woods Institute for the Environment. Dr. Maher’s work integrates field data, advanced computational models, and machine learning approaches to advance the sustainable engineering of earth systems, including soil-based carbon dioxide removal, water management, and carbon cycling in soil. Over two decades of research, she has developed methods to quantify enhanced weathering processes, greenhouse gas fluxes in soils, and subsurface carbon storage and mineralization, addressing global challenges in carbon and water management. Central to this work has been the creation of data science tools that combine scientific models with decision-making frameworks. She is a recipient of the James B. Macelwane Medal, a Fellow of the American Geophysical Union, and is recognized for her work on the carbon cycle in a permanent exhibit in the Smithsonian Museum of Natural History. Kate received her B.A. from Dartmouth College in Environmental Earth Science, an M.S. in Civil and Environmental Engineering from U.C. Berkeley, and a Ph.D. in Earth and Planetary Sciences also from U.C. Berkely. Prior to joining the faculty at Stanford, she was a Mendenhall Postdoctoral Fellow with the U.S. Geological Survey.
Summary:
Background: understanding soils and their chemical contaminants, and how they’re transported through the environment
Focus: using soils to store carbon (biochar and mineralized carbon) and accounting for any loss
Carbon removal is a required component of future climate mitigation
We need to reduce emissions and in addition to that, need to remove what we’ve emitted
The more we continue emitting, the more removal we need
100-300 Gt removal by 2100, ~10Gt/year
Many removals are temporary
Removals that re-release cause warming in the long-term future
Need approach that ensure long term (1000+ years)
Reality: in 2024 we’re not removing nearly enough
300Kt of biochar
8Mt of BECCS
We need a wide range of removal techniques across a wide range of permanence profiles
Current markets don’t ensure permanence
Need creditable CDR time curves
1000+ year permanence is creditable by markets
Shorter-term removal and probabilistic removal curves are very important but is not credited by markets
Need a way to forecast the future evolution of carbon persistence to enable full crediting of removal effects, incentivize action
CO2 removal via enhanced weathering
Rock alkalinity is enhanced: captures CO2
Rocks are slowly washed into the ocean, modifies the pH of oceans
Can quantify capture rates and long-term permanence in the ocean
Active work by many startups: Mati, Eion
Current science on rock weathering
Extensive measurement of long-term natural chemical weathering across the world
But natural weathering is too slow
Global Basalt weathering .04-.05 Gt / year
Global Silicate weathering .24 Gt / yeat
Our Goal: .5-5 Gt / year
Enhanced weathering looks to be much faster than natural weathering (reported rates .2-20 Tons CO2 / year / ht)
Analysis of mineralization capture and transport
Start by looking at capture of CO2 into solid rock, which becomes more alkaline
Then rock dissolved into water, transported via groundwater and rivers into the ocean
Soil pH is a key component of both CO2 removal and crop yields
Increasing soil pH is a standard farming practice since acidic soils have poor yield
Approach: TRACER
CrunchFlow: Reactive Transport simulator: https://github.com/CISteefel/CrunchTope
Soil pH Treatment and its physics using KSSL soil data: https://www.nrcs.usda.gov/conservation-basics/natural-resource-concerns/soil/kellogg-soil-survey-laboratory-kssl
Labeling system for tracking the chemical reactions
Analysis of impact of Ca-silicate and calcite on soil pH over time and depth
Shallow depth: spike in pH after initial application, stabilizes in 5-10 years
Deep: much more attenuated, shallow application has a smaller but more durable impact
Alkalinity export is time-dependent, need to worry about short-term atmospheric re-release
Key learning and future pathways
Mechanistic models + DGSA clarify what field data is needed
MRV is expensive: need to prioritize
Shallow soil measurements are misleading, don’t tell the whole story
Geochemistry operates on longer time scales than CDR credit periods
We credit based on short-term changes
But chemical transport from soil to ocean takes centuries