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The Land Sector Removals Standard raises the bar for how companies account for land-based emissions and removals, introducing clearer expectations around traceability, uncertainty, permanence, and monitoring.
Companies moving forward now are working to design programs that are credible today and resilient to stricter interpretations tomorrow.
Here’s how Regrow helps companies operationalize LSRS across the areas that matter most.
Solving for Removals
LSRS makes clear that removals must be grounded in robust science, with transparency around assumptions, data sources, and uncertainty. At the same time, it recognizes that fully empirical measurement everywhere is not yet feasible at scale.
Regrow supports removals quantification using Tier 3, process-based modeling that reflects real-world management, soils, and climate conditions. Where soil sampling or other empirical data is available, it can be used to calibrate and validate outcomes. Where it is not, Regrow helps companies understand feasibility, sampling needs, and tradeoffs.
This approach allows companies to move forward today while remaining aligned with future guidance on measurement and calibration.
Designing for Permanence and Long-Term Monitoring
Under LSRS companies must define monitoring periods, detect reversals, and establish clear accountability for long-term oversight. This is especially complex in agricultural systems, where practices, climate conditions, and sourcing relationships change frequently.
Regrow enables ongoing monitoring by combining remote sensing, management data, and process-based modeling to track outcomes year over year. This supports early detection of potential reversals, documentation of monitoring activities, and implementation of buffer or reserve approaches where appropriate.
For multi-buyer or landscape programs, Regrow can act as a shared technical infrastructure, supporting consistent monitoring across participants and reducing duplication as programs scale.
Quantifying and Disclosing Uncertainty Transparently
LSRS reinforces that uncertainty is a requirement to disclose and manage.
Regrow explicitly quantifies uncertainty within its modeling framework and documents assumptions in a way that is auditable and repeatable. Rather than hiding variability, Regrow helps companies understand where uncertainty comes from, how it changes with better data or traceability, and how to disclose it in line with LSRS expectations.
This gives companies confidence that reported outcomes are accurate within an acceptable window of uncertainty.
Making Traceability Practical
LSRS introduces stricter traceability expectations for removals, while allowing flexibility through impact traceability where physical traceability is not yet available.
Regrow supports multiple traceability levels, allowing companies to define spatial boundaries that reflect sourcing realities today. Using geospatial analytics and remote sensing, Regrow helps document traceability evidence, identify gaps, and prioritize improvements that materially affect accounting outcomes.
As traceability improves, emissions and removals calculations can be updated without rebuilding programs from scratch.
Getting Ready for What Comes Next
LSRS alignment is a multi-year transition that requires current programs to adapt and planned programs to evolve as implementation changes.
Regrow works alongside companies to phase implementation, stress-test assumptions, and adjust program designs as standards, assurance expectations, and market norms continue to mature. Together with our partners, we design systems that hold up over time.
Learn more about LSRS alignment and connect with us: hello@regrow.ag.
