Ex-Ante Carbon Modelling and DNDC Soil Modelling

Updated 2026-11-02 · 3 min read · By the akar.earth specialist team

Ex-ante carbon modelling and DNDC soil modelling for ARR, agroforestry and soil carbon projects in Southeast Asia, with transparent, auditable assumptions.

Ex-ante carbon modelling forecasts how many credits a project will generate, year by year, before any are measured. We build these forecasts for ARR, agroforestry and blue carbon projects, and run DNDC soil modelling for soil carbon and agricultural land management projects, with every assumption documented so buyers and auditors can follow it.

Who it is for

• Project developers who need volumes for a PDD, investment memo or offtake negotiation.
• Investors and buyers testing a developer’s projections.
• Agricultural supply-chain programmes exploring soil carbon or agroforestry removals.

The problem it solves

Projections drive money. Overstated volumes lead to undelivered credits and broken contracts. Understated ones leave projects unfinanced. Many models rely on generic growth curves or a single allometric equation that does not suit the species or site. Our ex-ante estimation guide explains where models usually go wrong.

What we deliver

Biomass carbon models (ARR, agroforestry, mangroves)

• Growth curves per species or species group, from published data and site plots where available.
• Allometry selection, using species-specific equations where published or the Chave et al. 2014 pantropical model with wood density.
• Survival, thinning, harvest and replanting scenarios.
• Methodology deductions: baseline, leakage, uncertainty and buffer, for example under VM0047.

DNDC soil modelling

• Site setup from soil, climate and management data.
• Baseline and project management scenarios.
• Calibration and validation against measured soil samples.
• Outputs formatted for VM0042 or other soil carbon methodologies.

For both

• Annual and cumulative credit tables, with conservative, central and optimistic cases.
• Sensitivity analysis showing which assumptions matter most.
• A methods note suitable for a PDD annex or investor data room.

How it works

1. Scoping. Project type, methodology, area, species or practices, and the decision the model supports.
2. Data assembly. Your planting plans and inventory data, plus literature and regional datasets.
3. Model build. In the AKAR Carbon Simulator for biomass, or DNDC for soils.
4. Review. A second specialist checks parameters, units and deductions.
5. Delivery and walkthrough. Tables, charts, workbook and methods note.

What you provide

• Area and boundary, species mix or management practices, and planting schedule.
• Any field inventory, survival counts or soil sampling results.
• Climate and soil data if you hold site-specific records.

Typical timeline

A biomass model for a defined ARR or agroforestry design typically takes two to five weeks. DNDC modelling typically takes longer because of calibration, often six to twelve weeks.

Tools we use

AKAR Carbon Simulator for biomass scenarios, AKAR Eligibility for land stratification, and field data from field data campaigns when calibration plots are needed.

How we keep projections honest

We default to conservative growth and survival assumptions unless site data supports better ones. We show the effect of uncertainty and buffer deductions explicitly, rather than reporting gross removals as if they were credits. We state which parameters come from literature and which from measurement, and we flag where a single assumption, such as survival in the first three years, drives most of the result. Models are versioned so later updates can be compared.

Next step

Try the free ARR carbon estimator for a first rough number and read the ARR hub. Then message us with your area, species and methodology for a proper model.