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Soil organic carbon: quantifying and incentivizing its accrual

This article is written for the layperson who is trying to understand soil organic carbon (SOC) quantification. It is long and gets into the weeds. Read it if you are someone who wants to dig into methods to quantify soil organic carbon and learn more about Nori’s approach to building a market that makes it possible to incentivize its accrual.

Maybe it’s just me — as someone who has gone down the soil carbon rabbit hole as a result of an obsession for developing and deploying practical tools to accelerate human action to remove Carbon Dioxide (CO2) from the atmosphere, and co-founder of a marketplace — Nori — that is working to make that dream a reality. But as we kick off 2020 in what is certainly a do-or-die decade for accelerating solutions to address climate change, it feels safe to say that carbon removal is getting hot, and storing more carbon in topsoil is leading the charge.

Why does SOC matter?

Let’s put things in perspective. In 2019, human activity emitted 37 billion tonnes (gigatonnes) of CO2). This isn’t counting the emissions feedback loops from forest fires or methane releases from a warming planet but put that aside for another time. Bottom line: because of our delay in reducing man-made emissions, without removing excess heat-trapping gases from the atmosphere — and storing any recovered carbon (“C”) or nitrogen (“N”) in the earth’s natural or man-made spaces, humanity appears unable to avoid the worst effects of climate change.

But the worst of these effects are still reversible. We just need to rapidly deploy solutions that emit much less and remove more C (and N) than we emit. Companies like Microsoft understand this, and are making big waves, announcing, this month, their commitment to go carbon neutral and then — even further — to remove the equivalent of all of the greenhouse gases they have ever put out there. Many ideas for different carbon removal techniques exist, at various levels of maturity, but keeping in mind the scale and urgency of the climate crisis, it is worthwhile to look to where most of the earth’s C is being lost, where rebuilding earthen C stocks might have the largest economic and environmental multiplier effects and our knowledge of how to rebuild carbon pools. After the earth’s core and our oceans, there is more C in the soils on the surface of this planet than anywhere else. There are roughly 850 gigatonnes of C in the atmosphere. There are about 3,170 gigatonnes of C in the terrestrial biomass, of which approximately 2,500 of which can be found in soils at a 30-centimeter depth.

According to Dr. Rattan Lal, a leading expert in soil science, the world has lost between 50 and 70% of the C that used to be held in topsoils, largely due to resource extractive (sometimes called “intensive”) methods of, food and fiber cultivation. This includes activities like decomposition, disrupting natural soil cycles with chemical inputs, planting monoculture crops, and accelerated soil erosion — a result of overturning the soil with plows.

Let’s geek out on soil C for a minute. Soils hold both inorganic and organic matter. Soil organic carbon (SOC) is the carbon component of soil organic matter (SOM). The most common factor for converting SOM to SOC is called the van Bemmelen factor, which is 58% (aggregated over all US soils). The USDA’s COMET-Farm platform uses this factor, as a default, to derive SOC quantities from SOM% estimates, but the organic carbon fraction can vary from 40 to 71% depending on a number of factors. SOM is a heterogeneous pool of diverse materials including fragments of litter, roots and soil fauna, microbial biomass, products of microbial decay and other biotic processes, and simple compounds such as sugar and polysaccharides. Oftentimes, when we’re out in the field talking to farmers, we speak in terms of SOM, not SOC. Farmers have learned that change in SOM%, over time, is a good indicator of past productivity and future yields. It’s important to note that the international standards for carbon markets focus on SOC, so that’s what I’ll use.

Here’s the good news: we know how to rebuild SOC and restore soil health in croplands. If we give ourselves 100 years to rebuild SOC stock levels in existing croplands around the world, those croplands have the capacity to draw 10 billion to 25 billion TCO2e out of our atmosphere, every year, for the next century. Businesses and individuals still have to emit less. But we have the capacity, know-how, and resources to hold global warming below 2 degrees C. (by 2100) if we move aggressively to rebuild the SOC stocks in global croplands.

Building soil carbon is happening now. It’s just not happening at scale. It is possible by keeping the ground covered year-round with a living root, leaving plant residue on the field, extending, combining, or diversifying crop rotations; reducing tillage; introducing livestock to terminate weeds, remove residual biomass and fertilize the soil; and applying beneficial microbes, biochar, and organic matter.

When we produce healthy and organic carbon-rich soils on agricultural land they: retain more water, release less pollution into rivers, lakes, and aquifers, and lose less soil to erosion (especially in extreme weather events), exhibit less compaction, increase biodiversity, and result in food that has greater nutrient density. So soils that are storing closer to their full potential for organic C are more productive and discharge less pollution in every scenario, and they are more resilient in the event of global warming. One could argue that even if you don’t believe climate change was a problem, it would be worth it to build soil carbon anyway — especially if, in 20 to 30 years, we will need to feed 1 billion more people than we do today!

OK so building SOC is good, but how do you quantify it?

We often say “Nori is standing on the shoulders of giants.” We aren’t building anything fundamentally new to quantify SOC. We are able to benefit from the great work of soil scientists and experts who have done critical work for more than 3 decades, advancing sampling and modeling techniques to provide metrics that allow us to administer a marketplace.

Nori’s approach to quantifying carbon removal and retention croplands builds on, among other sources: Carbon 180’s excellent summary, by Dr. Pete Smith et. al, “How to measure, report and verify soil carbon change to realize the potential of soil carbon sequestration for atmospheric greenhouse gas removal”; Dr. Keith Paustian et. al, “Quantifying carbon for agricultural soil management: from the current status toward a global soil information system”, and the Food and Agriculture Organization’s “Measuring and modelling soil carbon stocks and stock changes in livestock production systems Guidelines for assessment”.

Before getting into quantification method details for SOC, it’s important to note that SOC stocks are dynamic, even in the absence of changes in soil management and cropping practices. Soil type, soil density, crop mixes, microbial activity,, related respiration rate, temperature, and precipitation patterns all have major impacts on SOC fluxes. When designing a carbon removal market, that dynamic nature in the background, means changes need to be teased apart so that we can determine how much of observed SOC stock change is natural, and how much is a result of changes in practices. Moreover, because soil types can be so heterogenous, we must also account for locational variability and associated uncertainty in any SOC stock change quantification exercise. Furthermore, as a rough rule of thumb it’s fair to assume that as a result of respiration in agricultural soils about 10% of the organic carbon stored in soils will be lost, annually. Keep that in mind as we go through methods of quantification.

Direct Measurement

Direct measurement requires going out to a field and extracting soil cores. The cores are blended to form “samples”, then the samples are mixed, dried, sifted, bagged and sent to labs for testing. In the sampling stage, the number of cores that must make up a sample, and the points from which the cores are drawn, will depend on a number of factors, including soil type diversity and differences in elevation across each field. Just getting the number and distribution of cores correct for any given field takes some sophisticated statistical analysis.

It’s worth noting that most farmers subject their soil samples to many testsFarmers initially started gathering soil samples to determine nitrogen, phosphorus, and potassium (N, P, K) levels, soil acidity (pH) levels, and to get some indication of microbial activity.

In the earliest days of soil sampling and testing, 3 to 10 cores per field were thought sufficient to meet the farmer’s planning requirements. That grew to 10 to 30 cores per field if the field comprised a complex map if multiple soil types.

In some cases, today, farmers or their agronomist advisors might draw as many as 40 to 100 cores per field, once every two to five years. The best techniques for SOC require an estimate of SOC in mass per unit area to a specified depth, and the capability to estimate temporal changes in SOC stock associated with improved management. Tracking the management to the outcome is important, because it allows estimates for similar characteristics.

This video shows an Australian lab with excellent quality assurance/quality controls to handle samples from direct measurements to do valuable tests. There are quite a few soil tests, but for Nori, the gold standard for SOC are those derived from dry combustion with uncertainty estimates. This process works by pulverizing soil samples, weighing them, encapsulating them in aluminum foil, putting them in a furnace at 950℃, flushing the oxygen for complete combustion, and using an infrared elemental analyzer to detect CO2.

In the Paustian et. al, paper, it is noted that “Rather than using sampling designs that aim to quantify the total amount of SOC in a field, a more efficient and less costly approach is to measure SOC stock change over time at precisely located benchmark site. These can be resampled over time, reducing sample requirements by as much as 8-fold compared to simple random or stratified random sampling designs.”

Repeated soil surveys at benchmark sites

In line with the above sentiment to find cost efficiencies in soil carbon estimation, the NRCS has put together a database of characterizing sites in the National Cooperative Soil Survey soil characterization database through the Web Soil Survey. The Field Book for Describing and Sampling Soils outlines best in class guidance for professionals in the field to facilitate field observations and soil documentation. In the United States, there are pedons that collect very detailed information across hundreds of sites. Nori is most interested in those pedons which track a paired site for a similar soil type with conventional management practices tracked against additional carbon-removing practices. That allows for the projection of SOC accruals associated with management practices.

Example of a soil pedon, source NRCS

These big pits are scattered all around the world and they contain a window of information about soil types with characteristics like kind, quantity (percent of the area covered), size, contrast, color, moisture state, shape, location, hardness, and boundary. When characterizing soils in these sites, folks are on the lookout for redoximorphic features (RMFs). RMFs are color patterns in a soil caused by loss (depletion) or gain (concentration) of pigment compared to the matrix color, formed by oxidation/reduction of iron and/or magnesium coupled with their removal, translocation, or accrual; or a soil matrix color controlled by the presence of iron. Mottles refer to secondary colors that aren’t associated with compositional properties.

Source: Field book for describing and sampling soils

Remote sensing

Remote sensing allows us to infer estimations on carbon stocks without disturbing the soil. The most direct — and expensive — remote sensing method is an Eddy Covariance flux tower. Essentially this equipment takes measurements of CO2 concentrations and air movements that can be used to estimate the net gas exchange between the atmosphere and the land surface, a result of photosynthesis and ecosystem respiration.

An Eddy Covariance Flux Tower in the field. Source: USDA

While these techniques are useful for quantifying carbon flux, particularly in grazing lands and peatlands, because of their cost and technical requirements, they are mostly restricted to validating ecosystem models. The other end of the remote sensing continuum is through satellite imagery. Our friends and fellow ecosystem service market travelers Regen Network wrote an article about how they are using Sentinel 2 data to track the net ecosystem exchange. To do carbon accounting that complies with the International Organization for Standardization (ISO) greenhouse gas accounting guidance, these estimates should correlate to the actual management data.

Spectral measurement

Spectral measurement can include remote sensing (like from satellites and planes), but can also be proximal sensing that is static (like the handheld reflectometer tool used by Quick Carbon), or mobile (like the tractor-mounted sensors made by Veris Technologies). Nori will be contributing to this effort by allowing projects that are collecting spectral imagery to opt to share it with global libraries that can reduce the overall uncertainty of the SOC estimations. However, results from spectroscopic methods must be carefully calibrated for different geographic areas and soil types using dry combustion methods as a reference and are sure to include uncertainty ranges.

Models

COMET-Farm is the process-based modeling platform that Nori uses to make estimations in SOC changes from adopting conservation practices. The process-based model that underlies COMET is Daycent, which is able to simulate fluxes of C and N to the atmosphere.

The below graph shows an example of what a farm that would enroll in Nori could earn in terms of Nori Carbon Removal Tonnes (NRTs)—the sellable asset that represents one tonne of carbon removed—if they are switching from a conventional style of farming to no-tillage and cover crops.

A graphic depiction of how Nori uses a dynamic baseline to establish additionality

Effectively, using the COMET-Farm platform allows Nori to isolate practice-based additionality while accounting for the SOC stock changes. This ensures that Nori can use a conservative and dynamic estimate of what effect the practices listed above have on SOC accrual.

Why do marketplaces like Nori benefit from models to estimate carbon removal in soils?

“Data without models are chaos, but models without data are fantasy”

Patrick Crill made this comment to a conference of atmospheric scientists in 2014 (hat tip to Neville Millar at Michigan State University). This quote still holds true. Data and models go hand in hand. The challenge, therefore, becomes how to use models that can become more accurate by adding more accurate data to support the model and growing the dataset using the model.

There are plenty more details in Nori’s Croplands Methodology about how we can issue a NRT using COMET-Farm to establish a baseline. Nori employs a model to estimate soil carbon accrual for a few reasons. First, with a model it is free to get an estimate of how much additional carbon is drawn down from the adoption of certain practices. This is a huge improvement relative to existing carbon markets, where a project developer needs to spend thousands of dollars per project just to validate whether the project is a fit to sell the carbon asset. Building an integration with this model removes these costs.

Second, a model provides a dynamic baseline that enables the isolation of additional carbon removal activities from the normal variation that occurs in SOC fluxes. This means that when SOC goes up and down because of natural fluxes, we can satisfy the practice-based additionality criteria to meet International Organization of Standardization Greenhouse Gas Accounting Guidelines. A practice-based model allows us to compare practices that remove carbon against the norm, and also account for weather’s role in carbon fluxes.

Third, employing models provide a more direct benefit to the farmers participating in the program because of a time-lag with soil samples. If soil samples alone were establishing a baseline, it would take a minimum of 3 years to detect a change in carbon stocks from a direct measurement to receive any payment.

How does soil sampling fit into the Nori program?

It’s important to note that at a minimum, soil sampling occurs at year 10 of the Nori program. It is not an upfront requirement to enroll. However, participants who elect to provide soil samples to establish baselines must wait at least three years to see full accrual from this estimation technique. In a recent example, Nori and Locus Ag are partnering together on their Rhizolizer product which has the potential to increase NRTs issued per acre.

If a project owner is able to present credible, replicable soil sample test results that include uncertainty intervals, Nori will be able to modify NRTs generated. For illustration purposes, let’s say that the COMET-Farm platform finds a mean incremental SOC stock change value of 1.5 tCO2e/acre/year, on average for the last 4 years, with a +/- 50% uncertainty range (0.75 to 2.25 tCO2e/acre/year). But the high-quality soil sampling and testing method suggests a 3.0 tCO2/acre/year mean value for the same period, with a +/- 40% uncertainty range (1.8 to 4.2 tCO2/acre/year). Nori would, in these circumstances, issue 1.8 NRTs/acre/year to the project for the reporting period in question, which is within the uncertainty interval associated with the COMET-Farm estimate while at the low end of the soil sample test result uncertainty range. The 0.3 tCO2/acre per year difference will convert into restricted NORI tokens, after the resulting NRTs are sold, unless/until a more accurate re-estimate of the incremental SOC stock change is available.

What’s next?

Nori continues to work to develop a marketplace that makes it easy to have greater certainty on SOC increases associated with adopting practices that restore soil health. Our aim is to buttress up a system that is not bespoke to Nori, but contributes to advancements in an understanding of SOC uncertainty, and using models and measurements contributing to effective and scalable carbon removal for agricultural soils. The more the community who thinks about SOC accrual can get aligned in an open and transparent method on quantifying uncertainty and linking inventories with soil samples and additional carbon removal practice data, the more farmers who are optimally positioned to create a carbon removal commodity can lead the charge to reverse climate change!

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Nori is on mission to reverse climate change. This is our blog.

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Christophe Jospe

Christophe Jospe

Climate change entrepreneur and consultant. Recovering from carbon exuberance. I like to stir the pot.

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