> For the complete documentation index, see [llms.txt](https://open-carbon-protocol.gitbook.io/ocp-methodology-requirements/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://open-carbon-protocol.gitbook.io/ocp-methodology-requirements/sections/2.-conservativeness.md).

# 2. Conservativeness

All methodologies (and sectors) have areas of uncertainty and areas that need further research, such as uncertainty in direct measurement of emission parameters, assumptions and default values used in models, or unproven areas of new scientific research. These uncertainties (which may include baseline definition, parameter values, model structure, and measurement error) should be flagged for readers and potential users of the methodology, and mitigated by conservative adjustments.

Conservativeness refers to accounting for uncertainties by using lower-bound estimates or applying discount factors to calculations where necessary. The more uncertainty in any part of the methodology, the more conservative the methodology should be. Use this section to outline areas of uncertainty and describe how you will ensure appropriate conservative quantification techniques throughout.

Methodologies must include a quantitative assessment of overall uncertainty associated with credited outcomes, taking into account relevant sources of uncertainty. Where multiple sources of uncertainty are present, methodologies must describe how such uncertainties are combined or otherwise conservatively accounted for in credit quantification, including through conservative parameter selection, uncertainty deductions, discounting, or other justified approaches.

Expert reviewers assess whether the proposed treatment of uncertainty is sufficiently conservative given the activity type and data quality, and whether it supports the issuance of a conservative tonne of CO₂e.

The OCP is committed to being transparent about where uncertainties lie, while aiming to reduce them over time. We recommend using tools such as [CarbonPlan’s CDR Verification Framework](https://carbonplan.org/research/cdr-verification) for understanding uncertainties within removal pathways. We look forward to seeing similar tools emerge for the Avoidance and Reduction space.


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