The journey to a low-carbon future has created one of the greatest economic opportunities of our lifetime, however, this opportunity is not without its challenges. Publicly traded companies are feeling pressure to have their greenhouse gas (GHG) inventories and carbon strategies in place as both regulatory agencies and consumers demand better carbon transparency. Helping corporations achieve their net zero targets could create a $194 trillion opportunity for entrepreneurs and investors. The voluntary carbon markets, which provide a critical pathway to net zero for many companies, are expected to grow into a $10-40 billion dollar solution by 2030.
Yet, the multi-billion-dollar potential of the carbon markets may be misleading investors and buyers by ignoring the fundamental differences between financial accounting and carbon accounting.
In financial accounting, a dollar is a dollar. Uncertainty with dollars is not in the monetary unit, but it’s buying power which can fluctuate over time. We call this volatility, a measurement based on standard deviation principles from statistics. However, in carbon removal accounting, a tonne of carbon might not be the same as another tonne of carbon. The uncertainty arises with the precision and accuracy of the measurement methodology of carbon – which we call “margin of error”, a measurement also based on standard deviation principles from statistics. No one would argue they shouldn’t consider volatility when making financial investments, but we are ignoring volatility of measurement certainty when making carbon investments.
How bad can the problem get Unfortunately, uncertainty of over 250% is not unheard of. This is because of a concept called error propagation. Measurement error gets amplified by the errors within mathematic models (i.e. registry methodologies), combining carbon units (i.e. in the creation of carbon portfolios), or dividing them (i.e. creating derivatives). The large uncertainty in the current system means we can’t tell if we are merely comparing apples to oranges or apples to orangutans.
The problem with error propagation occurs in both carbon accounting itself as well as accounting for carbon offsets. In the subsequent sections, we show how error propagation creates challenges for accounting for what we emit as well as what we withdraw. As the SEC emissions reporting requirements evolve, it’s critical that climate products, services, and markets address accounting and measurement error to enable better market and product transparency, investment comparability, and an overall clear pathway for corporations to achieve net zero.
Deploying capital effectively requires reasonable certainty. An executive deciding how to better scale their company’s operations to become net zero, an investor deciding which technologies and sectors provide the best risk profile and return on investment, or buyers just trying to make better climate choices when offsetting their carbon activities, are not being provided with the fundamental information necessary to make an informed decision, let alone compare products or investments.
Accounting for Emissions: Greenhouse Gas Inventory and Emissions Factor Error
The error is larger than what most people think. Corporate emissions are measured and accounted for as Scope 1, 2, or 3. Scope 1 encompasses direct emissions, such as burning gas for cooking and fuel for driving. Scope 2 represents energy indirect emissions, such as the carbon from procured electricity from a utility. Scope 3 represents value chain emissions, including upstream and downstream carbon from the products we buy, sell, and discard. These emissions are calculated using emission factors from extensive databases. A strength of the system is that it is highly flexible to adapt to the unique situation of any company.
However, the system’s strength is also its weakness. The flexibility of reporting means that results can vary between 38 – 250%, and sometimes up to 4000%, depending on the databases used for emission factors and accounting choices made by the reporting entity. As shown in the below highlighted section of the IPCC guideline chart, emission factor uncertainty estimates range from a minimum of 1.5% to upwards of 150% for national-level inventories.
A second source of carbon error on the inventory side concerns the choices or assumptions corporations make as they build their inventories. Different choices and assumptions that are permitted by the GHG accounting standards can create results that differ by at least 38%. To use an example from the vehicle manufacturing sector, most vehicle manufacturers model the emissions from the use of sold products when reporting their Scope 3, Category 11 emissions. For this category, Toyota models solely gasoline combustion emissions over the lifespan of vehicles they produce. Ford does the same but adds the emissions associated with the extraction and production of gasoline in addition to gasoline combustion. The difference is what is known as well to wheel emissions (Ford), versus tank to wheel emissions (Toyota).
In comparing fleet performance, Ford’s number will always be larger than Toyota’s because they made a different reporting choice. These are best-in-class, similarly sized, directly competing companies with a deep understanding of carbon-based fuels, engineering, and GHG accounting practices. And both are correctly applying GHG standard methodology. However, their reported fleet carbon intensity cannot be compared at face value.
The issue of transparency and comparability becomes more muddled because emission factor uncertainty is compounded by the differing accounting choices companies can make. It’s not a problem of standardization – all companies are adhering to the rules of the standard. Uncertainty is part and parcel of this process because even if companies are diligently following the rules - the design of that standard makes an apples-to-apples comparison very difficult. These accounting standards have multilateral working groups focused on improving these problems and updating guidance regularly, unlike carbon credit markets.
Accounting for Removals: Carbon Credit Measurement Error
Carbon credits measure carbon being stored or redeposited back into products, natural environments, or underground. The models for issuing carbon credits are based on scientific methods of measuring the physical properties of materials, plant matter, or geological absorption of carbon. We know that each method of storage uses a different method of carbon measurement – with lab analyses being the least prone to error and visual or satellite methods being the most error-prone. When we add these different carbon credits together, error rates will propagate.
In a simplified example, let’s consider the multiple steps in the process of issuing and using afforestation credits. This includes everything from measuring multiple parcels of land, to issuing project credits, to combining different projects into portfolios, to buying, selling, retiring, and derivatizing credit portfolios. Despite the low range of measurement error across different forest areas measured with an optical density tool - we can see how quickly error propagates through the project as the different areas’ projected credits are combined.
After these credits are issued, they can be combined into a portfolio of other afforestation credits across the world. For simplicity’s sake we’ll assume all afforestation credits achieve the same +/- 30% margin. However, when we propagate that error margin through the portfolio, we achieve over +/- 67% margin of error.
While current controversies surrounding Verra’s methodologies and South Pole’s REDD+ credits providing 94% to 105% less carbon than their models predicted, these values may well be within the margin of error for afforestation project credits and portfolios – had error been propagated correctly. While the spotlight is on these climate companies today, they will not be the last if carbon market players don’t start propagating measurement error and reporting it correctly. Our industry must apply the essential calculation of measurement error already called out in the IPCC and GHG Protocol guidance. This applies to both GHG reporting as well as decarbonization solutions or credits.
Moving Forward
To achieve net zero goals and a 1.5oC target, it is crucial to know with a high degree of certainty that a tonne of carbon emitted is balanced by a tonne of carbon removed. However, currently both numbers have a very high degree of uncertainty. Considerable work is being done to improve emissions methodology error already, but carbon markets are far behind in addressing carbon measurement error.
Quantifying measurement error can enhance decision making. Disclosing it and the uncertainties associated with carbon credits allows investors and buyers to make more informed decisions based on their specific risk tolerance. Understanding risk can improve a company’s ability to compare and invest in carbon removal projects, that can range from afforestation to carbon remineralization. Together, this has the potential to address a core aspect of carbon product certainty for buyers.
Addressing the uncomfortable reality of carbon measurement error is crucial for the long-term success of carbon markets and achieving global climate goals. First, we should acknowledge and correctly propagate measurement error in both carbon accounting and carbon credit markets. In this way, companies can contribute to a more transparent, credible, and effective decarbonization pathway. As the world prepares for a low-carbon future, it is essential to address the uncertainties in carbon measurement and improve the reliability of the carbon credit markets to achieve meaningful progress in the fight against climate change.