What Makes a High-Quality Carbon Offset?

Avoiding Overestimation

Suppose that, for every 50 additional tonnes of CO2 that are reduced by an offset project, the project developer reports reducing 100 tonnes, and 100 offset credits are then issued to the project. Half of these credits would have no effect in mitigating climate change, and using them in lieu of reducing your own emissions would make climate change worse. Overestimation of GHG reductions can occur in several ways:

  • Overestimating baseline emissions. The first – and most subtle – way GHG reductions can be overestimated is if a project’s baseline emissions are overestimated. Baseline emissions are the reference against which GHG reductions are calculated, and are closely tied to additionality: they are the emissions that would have occurred in the absence of demand for offset credits.[1] Baselines are easier to determine for some types of projects than others. For a project that captures methane from a landfill and destroys it, the amount of methane that would have been emitted is generally equal to the amount that is captured and destroyed.[2] In contrast, there can be much greater uncertainty when estimating how many GHG emissions will be displaced on an electricity grid by a solar power project – leading to greater risk of overestimation if methods are not appropriately conservative.
  • Underestimating actual emissions. Many kinds of carbon offset projects reduce, but do not eliminate, GHG emissions. A project’s GHG reductions are quantified by comparing the actual emissions that occur after the project is implemented to its predicted baseline emissions. In the same way that baseline emissions can be overestimated, actual emissions can be underestimated – with both contributing to an overestimation of GHG reductions. One way actual emissions can end up underestimated is through measurement error. For example, determining the increase in the amount of carbon stored in trees in any given year is subject to measurement uncertainty, and sampling errors can lead to overestimating carbon sequestration (the equivalent of underestimating GHG emissions).
  • Failing to account for the indirect effects of a project on GHG emissions (aka “leakage”). To quantify GHG reductions, actual and baseline emissions are determined for sources (or sinks) affected by a project. Often, however, a project will have both intended and unintended effects on GHG emissions. If quantification methods fail to account for GHG emission increases caused by the project at some sources (even indirectly), then the total net GHG reductions will be overestimated. Unintended increases in GHG emissions caused by a project outside of its boundaries are referred to as “leakage.” The classic example is a forest preservation project that avoids the emissions caused by clearing one parcel of forest, but ends up shifting the production of timber through deforestation to other areas.
  • Forward crediting. Although rare, offset credits may be issued for GHG reductions that a project developer expects to achieve in the future. Such “forward crediting” is usually problematic, because it can lead to an over-issuance of offset credits if a project fails to perform as expected.[3] It can also pose issues if future events (e.g., regulatory changes) lead to additionality or emission reduction ownership concerns.

Finally, to control for all these possible causes of overestimation, it is important to monitor and verify a project’s performance.[4] It is important for measurement and data collection procedures – and for any calculations or estimates derived from these data – to be scientifically sound and methodologically robust. Furthermore, it is important for project monitoring data to be rigorously verified. Verification entails assessing the veracity of data provided by project developers, often through an audit of selected data samples. Carbon offset project developers have an incentive to report data that maximize the number of carbon offset credits they can sell. Verification helps to assure that reported data are accurate and do not overstate GHG emission reductions.


[1] Again, a common misconception is that the baseline for a project represents what would have happened “in the absence of the project.” However, it is essential to evaluate whether a proposed project is itself the baseline (i.e., is not additional), and therefore will generate no emission reductions.

[2] Assuming that the project is additional and that the project itself does not affect the rate of methane generation at the landfill – for example, by creating a “bioreactor” landfill.

[3] See, for example, Offset Quality Initiative (2008).

[4] This process may include collecting and verifying data needed to estimate a project’s baseline emissions.