CASE STUDY
Carbon Footprint of Coconuts Produced with Regenerative Farming Practices
Our client aimed to strengthen the credibility of their sustainability claims by updating the carbon footprint of coconuts produced under regenerative farming practices—integrating improved emission factors that capture soil‑based carbon sequestration and establishing a continuous monitoring framework to ensure transparent, data‑driven environmental performance over time.
Key Takeaway
Regenerative practices offer real potential for soil carbon gains, but achieving net climate benefits requires careful management of CH₄ and N₂O emissions that may rise as soil conditions change. Robust monitoring and manure management practices are therefore critical for farms seeking genuine emissions reductions.
PROJECT SCOPE
Update the emission factor for a portfolio of 600+ farms producing organic coconuts from cradle-to-farm gate, while including soil organic carbon (SOC) dynamics from regenerative practices.
Provide guidance for soil sampling across selected representative farms in order to model model SOC changes for frequently occurring combinations of regenerative practices. This includes providing guidance on soil sampling locations, quantities, and lab testing parameters.
Develop a continuous monitoring framework and data collection templates to support client in on-going updates of the emission factor.
REGENERATIVE PRACTICES ASSESSED
Cover cropping, mulching, integrated crops, integrated animals (aquaculture), on‑farm biomass recycling, and windbreaks/wind barriers.
MODELING TOOLS USED
A combination of a custom Excel-based tool with modelling in DNDC was used in this study.
DNDC (Denitrification–Decomposition)
Role: Primary soil biogeochemical model used to simulate soil organic carbon fluxes, N2O and CH4 emissions at site level for each sampled soil profile.
Strengths: Allows site‑specific soil parameter inputs (SOC, texture, bulk density, pH, moisture), daily resolution, ability to include manure amendments and other farming practices.
Limitations: not well-equipped for handling of intercropping systems, limited modelling for submerged/wet soils and aquaculture, limited handling of repeated harvest cycles specific to perennial harvesting, and limited transparency because code is not fully open‑source. Work-arounds and proxies were developed where required.
Custom Excel‑Based LCA Tool
Role: Life Cycle Inventory (LCI) compilation and farm‑gate carbon footprint calculations (inputs × mapped emission factors) normalized to 1 kg coconuts; used to combine upstream inputs, transport, energy, direct emissions and to incorporate DNDC SOC results.
Strengths: Transparent, non-black box approach, user-friendly, and easily modified by users not familiar with more commonly applied LCA software.
Limitations: User error may occur after handoff, so it may require careful version control and QA/QC.
WHAT WE LEARNED
Farms applying several regenerative practices, but especially those that apply both mulching and integrated crops, showed the largest soil organic carbon gains over the one-year modelling period.
Farms assessed applied cover crops at coverages ranging from 0-100%. Increasing cover‑crop coverage correlated with lower net emissions.
Manure application rate is a sensitive driver of N2O and net emissions in the soil model.
Some regenerative practices (integrated animals, water/wetland conservation, the traditional nutrient cycling practice of dredging) may provide benefits that are not able to be modelled by currently available soil modelling tools. Robust monitoring and methodological advances are needed to quantify them fully.
OUR IMPACT
We provided clear evidence of where regenerative practices are delivering measurable carbon benefits—and where advances in monitoring and modelling are required to accurately reflect their total climate impact.