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Documentation Index

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

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Mangrove Systems is excited to work with you to configure Mangrove for your project operations. We’re committed to being a strong partner to our customers and look forward to supporting your important work. An upfront configuration period is generally best practice in order to set the production modeling up for your team to get the most out of Mangrove. There are aspects that require tight collaboration between you and Mangrove, such as co-designing production accounting models - this guide serves as an introduction to key concepts of the Mangrove framework.

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dMRV

MRV stands for measurement, reporting, and verification. It’s sometimes referred to as MMRV, which adds monitoring. As adopted, the definitions vary somewhat from program to program, but the ultimate purpose - to ensure accuracy, transparency, and accountability for carbon initiatives - remains the same. MRV plays a critical role in both voluntary and compliance markets. It helps ensure integrity in the markets by providing a standardized approach to tracking emissions and reductions. It is crucial for maintaining trust among market participants, ensuring that carbon removals represent actual carbon removals. dMRV stands for digital MRV - this is the implementation of MRV in a completely integrated data pipeline, from the data generated by meters and sensors, to ongoing net GHG quantification by models, certification of the accounting data, and continuous issuance and addition of units to a deliverable inventory of credits. With dMRV, projects can turn their real-time operational data into auditable data packages, and drive quicker conversion into revenue or reporting than traditional months/years-long commercialization cycles. You can read more in our introduction to MRV.

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The Building Blocks of Best-In-Class dMRV

The regular project development and production process consists of several key stages from molecule to market, driving the accounting from operational data collected across the project boundary, to recording deliveries of verified credits to buyers. Mangrove is designed to address every step of the credit issuance cycle, with these key dMRV building blocks:

Data collection

Projects can aggregate datapoints from data sources across their project boundary, through various ingestion pathways

Production accounting

The aggregated data is run through a data flow of production and quantification models to generate calculated outputs and production batches with underlying MRV data.

Compliant reporting

Reporting that is compliant with active value streams can be generated from the production accounting and submitted to verifiers and to registries.

Credit inventory management

Manage all forecasts and issued credits in one place

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Production accounting

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From collected data, to production batches

MRV and production accounting is defined per Project in Mangrove - this allows for data ingestion to be configured specifically for the measurement environment, and specific quantification, of that Project. For example, a project developer may operate a project in the U.S., with data parameters in imperial units and a local set of sensors, and another project of a different pathway in Europe, with a different set of inputs, units in metric, and different SCADA systems as data sources. dMRV for both projects are equally configurable within Mangrove. Production accounting is done through three steps: (1) collecting the data inputs, and (2) running the inputs from a particular production period through a data flow of models. The outputs of the accounting are calculated data points, and a series of production batches with underlying MRV calculations and data. (3) The batches are allocated to issuances on the credit inventory.

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The Data Flow: Production and Quantification Models

The calculations and data associations to generate production accounting are represented in Mangrove by 2 main types of models: production models, and quantification models.
  • Each production model represents a layer of calculations within the project’s operational activity. A project can have one or multiple production models in a data flow, depending on the depth of calculations required. The output of production modeling is the accounting of the project’s gross production
    • For example, a project’s quantification could require 3 models: (1) a primary production model, receiving calculations from (2) a specific emissions-allocation-factor model, and (3) a model for blended mass balance. The outputs of production modeling flow seamlessly as inputs into the quantification model
  • A quantification model performs the next phase of calculations, receiving the project’s gross production accounting over a certain period, and generating the net carbon accounting. This involves layering in LCA calculations, to calculate the emissions across all required stages of the project boundary, and the acceptable emissions factors applied.
    • An example is the net GHG quantification equations within the CA-GREET model that drive LCA calculations for projects being certified through the CA LCFS compliance market
    • The quantification model is specific to the value stream - it is the acceptable quantification that is defined by that standard
A value stream is a program that the project developer has selected to commercialize the carbon production of a project. Value streams could be voluntary programs (e.g. VCM registries like Isometric or Verra), compliance markets (e.g. LCFS), or tax programs (e.g. US IRS tax credits)
Taken as a full data flow, these models are digital versions of a carbon methodology or protocol. The models store the required calculations through a flow of nodes and operators. A set of inputs (measured, calculated, or standard variables from resource libraries) are needed within each production period, in order to output the production accounting.
  • Production accounting is done on a time-based, or id-based, approach: Time-based production accounting quantifies the gross carbon production between set periods of time. For example: liquefied CO2 that is captured, transported, and injected on an ongoing basis within a CCS network. Each production batch reflects the MRV and accounting within its production period
  • ID-based production accounting quantifies the gross carbon production that results from processing of specific units of production. For example: biochar carbon removal is driven by the delivery and end use of individual loads of biochar. Terrestrial storage of biochar is driven by the sequestration of individual loads of biomass. Each production batch reflects the MRV and accounting attributed to the Tracking ID of the underlying unit of production
At initial configuration, Mangrove Systems frequently works hand-in-hand with the project developer to co-design the production modeling, which Mangrove then digitizes and loads into the project, along with the quantification modeling that is digitized from the value stream’s methodology. After configuration, projects can work with Mangrove to update the models to reflect the latest science, instrumentation environment, or changes in project boundary.

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Data Inputs: Types of inputs

As a result of defining the models, the project has an inventory of data parameters that need to be collected or entered into the Project to drive production accounting. These parameters span the full universe of operational activity occurring across the project boundary. A non-exhaustive list of examples of these parameters:
  • Baseline data - e.g. the baseline soil mineralogy, or water pH, or initial level of biochar production that needs to be excluded to derive additional carbon accounting
  • Input/feedstock data - e.g. feedstock quantities, sources, biomass types Sequestration data - e.g. CO2 injection rates, amendment application rates, end use locations
  • Energy usage - e.g. volume of fuel, grid-mix electricity used within a period
  • Transportation data - e.g. average distance traveled to transport feedstock
The necessary set of data parameters are very specific to the project’s removal/capture pathway and technology.
These data parameters are often defined under data parameter tables, or monitoring tables, within the MRV section of a carbon methodology.