PanXchange Blog – September 2021
ESG interest, by way of carbon offset credits, is booming in various industries, spanning energy, infrastructure, transportation, and even agriculture. However, there are unique barriers to an efficient market for carbon credits from agriculture, particularly those derived from croplands.
Voluntary carbon credits sourced from agriculture are currently priced between $15-$30 per credit (or per ton of CO2e) and could easily quadruple in price over the next couple of years based on demand. Given the number of credits generated from typical cropland projects and the cost of generating credits, aggregating farmland into larger “megaprojects” can improve the economics by capturing economies of scale. This is especially true when following some more stringent and costly methodologies to generate carbon credits. While there are certainly opportunities to capture economies of scale, there are disadvantages to this approach from a logistics and project management perspective, especially as farmers naturally have unique methods of operations and relations with various stakeholders.
Another key issue faced when producing carbon credits on existing cropland is what is known in the ESG world as the common practice test. The common practice test asserts that if you implement a regenerative practice on your farm, yet the practice is common in farms proximal to yours, this would fail to meet the requirement for additionality needed to earn carbon credits. The PanXchange team believes that in order for this market to create more economically viable solutions to incentivize a proactive response to climate change, standards need to be set to not only create meaningful carbon offset products but to ensure that they are marketable.
Additionally, another major debate in the world of SOC carbon credits is the debate between measurement and modeling. For firms that use the modeling approach to generate carbon credits, they typically require an initial measurement to calibrate the field measurements with scientifically peer-reviewed software to model changes into the future and can issue credits upon verification that detailed inputs to the model are, in fact, sound throughout the process. While congruency with and support from government agencies such as the USDA or United States EPA in calculating greenhouse gas inventories leads to a high level of credibility, empirical measurements (even remotely observed ones) are always going to be more credible than modeled values.
Given the nascent nature of the carbon offset credit market, particularly with regard to cropland projects, other firms aim to provide their buy-side clients greater assurances that measurements are accurate. They do so by providing empirical soil carbon measurements at the outset of the project, as well as on an annual basis throughout the project’s life cycle (typically 10 years). They then typically use modeling software to estimate and pre-issue a very conservative portion of the estimated carbon credits generated to speed up their credit generation timeline. However, while this method proves to be more credible, it is also more costly. It will be interesting to see as the ESG landscape evolves, how market participants balance the tradeoffs between meaning, credibility, and marketability when issuing carbon offset credits.