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Accounting Academy

MODULE 1: Fundamentals

MODULE 2: Calculations

MODULE 3: Batch Partitioning & LCA

MODULE 4: Mass Balance with Ledgers

MODULE 5: Integration Testing

MODULE 6: Advanced Patterns & Production

Documentation Index

Fetch the complete documentation index at: https://docs.mangrovesystems.com/llms.txt

Use this file to discover all available pages before exploring further.

What you’ll learn in this lesson:
  • Map methodology concepts (activity data, emission factors, monitoring cycles) to Mangrove components
  • Identify which Mangrove component corresponds to each part of a carbon methodology
  • Translate a methodology’s data parameter table into Mangrove’s data structure
Carbon accounting methodologies define what to measure, how to calculate, and how to report. Mangrove is built so that these concepts map directly onto its core structures. Once you see the mapping, configuring a project becomes a matter of translating your methodology into Mangrove building blocks.

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Methodology concepts and Mangrove structures

Methodologies typically specify data parameter tables or monitoring tables in their MRV section. The required inputs, factors, and equations align with the following Mangrove components.

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Datapoints ↔ Activity data and measurements

In the methodology: Activity data and measurements — fuel consumption, area surveyed, energy readings, mass delivered, moisture content — are the raw inputs required to run the quantification. In Mangrove: These become datapoints. Datapoints live inside:
  • Events — for ongoing, batch-varying measurements
  • Static inputs — for values that stay constant over time
The data parameters your project needs are determined by your models and often correspond directly to the methodology’s monitoring or data parameter tables.
Examples: feedstock quantities, sequestration rates, energy usage, transportation distances, baseline data.

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Static inputs ↔ Emission factors and factor libraries

In the methodology: Emission factors, conversion factors, and constants (e.g., tCO2e per kWh, tonnes per pound) applied across many calculation periods. In Mangrove: These are static inputs — datapoints that remain constant over time and feed into calculations across multiple batches. Configure them in Data Inputs > Static Inputs . Examples:
  • Grid electricity emission factor (e.g. 0.00043 t/kWh)
  • Conversion factor (e.g. metric t/lb)
  • Facility-level parameters (e.g. ”% of facility electricity related to carbon production”)
Resource library inputs are a variant — they come from Mangrove’s Resource Libraries (e.g. global warming potentials) and provide shared, science-based variables.

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Batches ↔ Monitoring cycle and reportable units

In the methodology: The monitoring cycle defines how often data is grouped for quantification — per delivery, per day, per month — and what the reportable unit of production is. In Mangrove: These become batches. Each production batch groups datapoints and calculations for a defined time period or boundary, mirroring the monitoring cycle. Two partitioning approaches exist:
  • Time-based — MRV within a production period (e.g., daily injections)
  • ID-based — MRV for a specific unit of production (e.g., a delivery)
See time-based vs ID-based accounting for details. You generate batches by running the accounting dataflow over the desired period.

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Ledgers ↔ Chain of custody and mass balance

In the methodology: Chain-of-custody and mass balance rules define how material moves between stages (e.g., feedstock received → production → delivery). In Mangrove: These are ledgers (mass accounts). Mass balance accounting uses ledgers to track accumulation and use of material at each stage. Batches credit or debit ledgers, and allocations between ledgers support traceability.
Not every project needs multiple ledgers — a single ledger is often sufficient when there is only one reportable stage.

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Models ↔ Quantification equations and logic

In the methodology: The equations and logic that combine activity data and emission factors to produce gross and net emissions or removals. In Mangrove: These become models. A model is a set of calculations built as a tree of nodes — inputs, operators, and outputs. Two types: Models are the digital version of your methodology’s formulas.

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Reports ↔ Standardized output for the reporting period

In the methodology: A standardized package of data and documentation for a reporting period (e.g., quarter, year). In Mangrove: That package is a report. A Report shows a project’s activities, carbon accounting, and outcomes for a reporting period. Reports are submitted for verification and credit issuance.

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Issuances ↔ Verified credit volume

In the methodology: A verified volume of credits that can be held, traded, or retired. In Mangrove: That outcome is an issuance — a group of active, tradable credits in your inventory , representing verified carbon production for a specific period.

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Check your understanding

Static Inputs. Static inputs hold values (like emission factors and conversion constants) that remain constant over time and feed into models across multiple batches.
Time-based batches group data by production period (e.g., daily injections). ID-based batches group data by a specific unit of production (e.g., a single delivery or production run).
In the next lesson you will work concretely with events and datapoints — defining event types, required and optional fields, and attaching evidence.