<figure><img src="image_131.png" /></figure>

Key characteristics of each MRV methodology (see here) can be used to acquire key information about individual MRVs and compare them. However, while this gives information about key aspects, a comparison of MRVs is cumbersome because of the large number of characteristics involved. Therefore, it would be helpful to reduce the multi-dimensional space in which the MRVs are scored to only two dimensions. As a result, each MRV would take up a position in a two-dimensional plane, where MRVs that have similar characteristics are near and where MRVs that have vastly different characteristics are far apart. This dimension reduction can be achieved with a statistical technique known as multidimensional scaling (Borg and Groenen 2005; Cox and Cox 2020). Here we applied multidimensional scaling using the 'cmdscale' function of the 'cluster' package of the R software for statistical computing (Team 2021).

Multidimensional scaling requires a dissimilarity matrix as input. This is a square matrix that has as many rows and columns as there are MRVs, and whose value at row *i* and column *j* stores the dissimilarity between the *i*-th and *j*-th MRV. The dissimilarity between two MRVs is derived from the characteristics of the two MRVs. Since the characteristics of MRVs listed in Table 4 are measured on a nominal scale, common Euclidean distances cannot be computed. We therefore used the Gower metric instead (Gower 1971). This simply assigns distance 0 if the two MRVs have the same value for the characteristic, and distance 1 if they are not the same. This is done for all characteristics and the average of all distances defines the dissimilarity between the two MRVs. It is possible to assign weights to the characteristics and thus allow some characteristics to have more influence on the final dissimilarity metric than others. We did not do this here and assumed that all characteristics are equally important, which is a simplification.

The results of the multidimensional scaling are shown in Figure 7. The figure shows that the MRVs are fairly uniformly distributed in the two-dimensional space and that there are no clear clusters or extremes, although some patterns can be observed. For instance, Gold Standard and GSOC-MRV are quite close, indicating that they share key characteristics. Indeed, both MRVs aim at the voluntary carbon market, are developed for the whole world, encompass all Tier levels, include quality assurance, are result-based and agree on most of the requirements (Table 4). Other clusters of similar MRVs are: NL-SNK, US-SEP and BC-SCM (all three are developed for a specific country or countries, make use of process-based models, are result-based and have a data retention/sharing policy); VM0006, Nori and Plan Vivo (which all focus on SOC stock change, have a specific country or countries as geographic scope, use historic land management as a baseline setting and do not require ground truth SOC observations). VM0042 is the most isolated MRV. This could be because unlike other MRVs it scores 'low' or 'No' on most requirements. This explanation is supported by the fact that CARSSE, which is opposite VM0042 in the two-dimensional plane, scores 'Yes' for almost all requirements. It is also interesting that VM0042 is not very close to VM0006, although they are in the same quadrant of the plane. This can be explained by the fact that VM0006 is for 'forest lands' whereas VM0042 is for 'croplands'. Regen is another MRV that is at the outside of the two-dimensional plane and quite isolated from other MRVs. This could be because it is only focussed on grasslands, requires a high frequency of ground truth SOC observations for reporting and uses hybrid models. None or only a few other MRVs have the same values for these characteristics.

It should be noted that five out of the 27 key characteristics are related to an MRV 'requirement'. Since no weights were applied these characteristics together have a strong effect on the outcome of the multidimensional scaling, for example five times stronger than 'Purpose of MRV' or 'Ecosystem(s) covered.' There is much to say for reducing their influence by assigning weights. Likewise, many users might wish to

<figure><img src="image_132.png" /></figure>
<figure><img src="image_133.png" /></figure>

ORCaSa
Because soil carbon matters

assign a higher weight to characteristics such as 'Target depth interval,' 'Geographic scale' and 'Tier level' than to characteristics such as 'Reporting periods' and 'Frequency or reporting'. Assigning weights involves subjective choices but so does the a priori decision about which characteristics are included in the analysis. Hence, it could be worthwhile to organise stakeholder workshops to jointly define and refine key characteristics of MRV methodologies and associated weights and evaluate the sensitivity of the multidimensional scaling results to choices made.

Multidimensional scaling MRV guidelines

<figure><img src="image_134.png" /><figcaption>Figure 7. Position of considered MRVs in a two-dimensional space after application of multidimensional scaling to MRV characteristics as scored in Table 4.</figcaption></figure>

<figure><img src="image_135.png" /></figure>

The ORCaSa project has received funding
from the Horizon Europe Programme under
grant agreement n° 101059863.
<figure><img src="image_136.png" /></figure>
<figure><img src="image_137.png" /></figure>

# 4. Towards an integrative and multi ecosystem MRV framework for SOC stock changes

## 4.1 Motivations toward a more unified but adaptive MRV framework for SOC stocks assessments

As illustrated by the previous sections, regarding soil carbon MRV, there is a wide variety of application contexts (NDCs, CAP, voluntary C market, insetting), ecosystems (e.g., forest, grasslands ...), frameworks, guidelines, methodologies for monitoring and verification and even more tools. Currently, none of the guidelines, frameworks or tools allow to address all ecosystems or context of MRV. For instance, MRV frameworks for voluntary C market generally require following projects (e.g., carbon farming) continuously for a duration of 5 to 10 years. Alternatively, in Australia, a landholder can select 25 years and 100 years at the time of project registration. 25 years should provide good evidence that SOC has changed due to management activities as change in SOC is slow under a given management. However, the 25 year projects will have higher discounts compared to 100 year registered projects. In, in practice, in Australia more projects are registered for 25 years due to economic return times.

In the context of insetting, a company that will sell for instance soft maize may contract a farmer for only one year and one plot meaning that it will need to quantify SOC stock changes and pay the farmer accordingly based on the carbon farming practices the farmer has implemented only for that year and that plot<fnref n="57" />.

The following year, the company may contract another farmer to produce soft maize. Therefore, the implication in term of monitoring is that for insetting the framework and methods may require an annual assessment, reporting and verification of the SOC stocks changes. Typically, in this context it is unrealistic to rely on an in-situ soil sampling approach to measure SOC stock changes (which is often mandatory in the context of voluntary carbon market) and a carbon budget component modelling approach may be the only method applicable.

This example shows that even for a given type of ecosystem, currently several frameworks, methodologies or tools may be used depending on the application context. This generates risks of inconsistency in monitoring the evolution of soil carbon stocks between the schemes and it could lead to awkward situations if the same actions (e.g., a farm engaged in new carbon farming practices) were evaluated or financed through two different sources (e.g., CAP and offsetting program). Some would argue that for reasons of non-additionality

<figure><img src="image_138.png" /></figure>

<footnote n="57">⁵⁷ Note that GGP Scope 3 reporting can be at project level which means that soil C changes associated with commodity can be reported from an entire region, i.e., regional baseline versus regional change. Hence, what is needed are tools and approaches to support different forms of MRV - and not to assume that it all comes from the monitoring the same fields T₀ to Tₓ. Hence, the soil sampling needs to reflect the different approaches e.g., be sufficient to model and sufficient to validate change at different scales.</footnote>
<figure><img src="image_139.png" /></figure>

the same action should not be financed through several schemes (e.g., CAP and carbon offset program), but the reality is that currently the price of a tonne of CO2 on the voluntary respectively compliance C market (which differ widely) do not often offset the cost of implementing practices (other sources of financing may be needed) and the issues of non-additionality are not fully resolved. Concerning carbon farming in Europe, the European Commission hasn't clarified yet the rules in terms of additionality and the sources of financing (e.g., public through CAP subsidies, private through the voluntary carbon market, a hybrid approach). Given the urgency in implementing climate actions, and the fact that the CAP is now performance-driven, it would be relevant to base support measures on results rather than on actions. However, all the financial risk would be on the side of the farmer (who may do his best to implement C farming practices, e.g., cover crops, but that may fail to store C because of a bad climatic year). At the opposite, in the case of action-based payment (as in the previous CAP), all the risk is on the side of the policy body (that pays for actions that may not result ineffective SOC stock increases). For those reasons, the NIVA project suggested a hybrid scheme<fnref n="58" /> where a farmer would get a part of the payment based on actions to increase SOC stocks in the soil (e.g., annually through CAP subsidies), and bonus payments based on results (an effective increase in SOC stocks) through the voluntary C market (e.g., after 5 years of implementation of the C farming actions). In such a hybrid market scheme, the farmer and policy body would share the risk of non-delivery and ideally, the same tool for monitoring should be used (or at least the same kind of methodological approach) for both the payment based on action and results to ensure consistency in the hybrid scheme (e.g., the TIER 3 approach developed in NIVA based on the AgriCarbon-EO processing chain) although the assessment could occur with different temporalities (yearly but during 5 years for the CAP, after 5 years for the voluntary C market).

The examples presented in the two previous paragraphs illustrate the need for a harmonised but flexible monitoring framework. Other considerations are related to the need for consistency in SOC stock changes quantification 1) between countries that may use different Tiers approach to evaluate their NDCs (need for consistency between countries and between the Tiers), and 2) between scales (e.g., countries, regions, local offsetting project) and contexts of MRV (e.g., NDC's, C farming projects) (for more details, see page 22-23 in the appendix of<fnref n="59" />). Note that Tiered approaches/tools currently used for NDCs (following the IPCC guideline) and for the CAP (e.g., NIVA's project C budget indicator approach) may differ.

Another reason for proposing a more unified framework for MRV of SOC stock changes is that most landscapes are composite (several land covers and land uses). A unified framework would reduce the risk of leakage or double accounting. Also, they are similarities in key processes (e.g., photosynthesis) of the main ecosystems (e.g., forest, crops and grasslands) which can lead to the development of approaches/tools with similar architectures or composite block (and therefore relying, at least partly, on similar guidelines). For instance, some processes like photosynthesis or soil organic matter mineralisation can be simulated with similar tools/codes for different land uses, similar data can be used as inputs (e.g., climatic data, high resolution optical remote sensing data) and the same observation networks (e.g., ICOS flux tower networks) can be used for validation or uncertainty assessments of the models/building blocks at different ecosystems.

<figure><img src="image_140.png" /></figure>

<footnote n="58">⁵⁸ https://www.niva4cap.eu/wp-content/uploads/2022/12/NIVA-Policy-Brief-nr.-5-Agro-environmental-indicator-carbon-D1.0.pdf</footnote>

<footnote n="59">⁵⁹ https://www.circasa-project.eu/content/download/4158/40011/version/1/file/CIRCASA_D3.1%20SRA.pdf</footnote>
<figure><img src="image_141.png" /></figure>

ORCaSa
Because soil carbon matters

Finally, all those elements point toward the need of a more unified but adaptative (e.g., with a Tiered approach, monitoring with various temporalities) framework for MRV of SOC stock changes. Because of that ORCaSa aims at producing a cookbook for a blueprint of an MRV framework for croplands SOC stock changes (Task 4.2) and at building an integrative and multi-ecosystem MRV framework for SOC stock changes (Task 4.3).

## 4.2 Need for a new modular and integrative multi-ecosystem MRV methodology for SOC stock changes

The analysis of the current needs in MRV for different and sometimes new contexts (CAP, offsetting, insetting) but also of the current MRV frameworks, guidelines and building blocks highlights that the main challenges (e.g., large scale, high resolution, repeated & short term assessment for the CAP) concern the monitoring component of the MRV.

### 4.2.1 Monitoring

Through the frameworks and guidelines survey, we observed that these can be split into: 1) soil MRV that combine soil C stocks with soil derived GHGs and 2) full ecosystem C assessment that include above ground biomass. Some MRVs are too focused on the soil itself, overlooking the fact that organic carbon inputs mainly come from the vegetation. For instance, in the French LBC methodology for arable land, no clear guidelines or protocol are given for estimating crop or cover crop biomass and its fraction that returns to the soil. As a consequence, large uncertainties in the SOC stock changes estimates can result from rough biomass estimates (e.g., the use of regional statistics of cover crop biomass is suggested with discount in the LBC method) or inappropriate methods/protocols for estimating it. Also, methods for quantifying SOC stock changes generally fail to consider the spatial variability in biomass production and restitution to the soil that can be cause by pest, topography, microclimates etc. which is surprising as intra-field heterogeneity is a well-established issue in agricultural applications (e.g., Blackmore et al. 2003; Weiss et al. 2020). Wijmer et al. (2023) showed that assimilating averaged LAI at a plot level instead of high-resolution LAI products (10m) could cause a significant underestimation of the winter wheat biomass estimates (i.e., impact of input spatial support depends on the scale of the MRV application.) Overall, very few guidelines, methodologies or tools rely on biomass quantification by remote sensing (or by hybrid modelling approaches assimilating remote sensing data) to map its spatial variability in an attempt to 'feed' the soil models with more accurate estimates of crop residues. Reasons are probably manyfold: lack of awareness of remote sensing potential by the soil modeler's community, lack or inappropriate remote sensing data (e.g., need for L band satellites to quantify biomass for highly productive forest) or ready to use biophysical products derived from remote sensing (e.g., high resolution multitemporal LAI products) and also, most ecosystem and soil models were not designed initially for spatialised applications but for local (plot, farm) applications. For such models, assimilation of remote sensing data can correct the model's trajectory (e.g., Ferrant et al. 2014) but as shown by Casa et al. (2012) for cropland or by Le Maire et al. (2005; 2011) for forest, upscaling processed based model initially

<figure><img src="image_142.png" /></figure>

The ORCaSa project has received funding from the Horizon Europe Programme under grant agreement n° 101059863.
<figure><img src="image_143.png" /></figure>

ORCaSa
Because soil carbon matters

developed for local applications model by assimilating remote sensing data is challenging because those
models need many input data (on soil, management etc.) and require many parameters to be set. Based on
those considerations, current C stocks estimates may benefit from remote sensing assimilation but a dedicated
new generation of models (e.g., SAFYE-CO2; Pique et al. 2020ab) tailored to upscaling the C budget
components may have to be developed.

Monitoring may involve several building blocks described here above in Section 2.2 and illustrated by Figures
2 and 3. Yet, concerning cropland, the frameworks proposed by Paustian et al. (2019) and Smith et al. (2020)
did not clearly describe how to make the different building blocks interact and what the ‘scalable quantification
platform’ mentioned by Paustian et al. (2019) should be. For those reasons, in ORCaSa we aim at proposing
a ‘cookbook for a blueprint of an MRV framework for croplands SOC stock changes,’ adapted to different
context of MRV (CAP, NDCs, voluntary C market, insetting) and levels of availability/accuracy of farmer’s
activity data. Those cookbook and prototype built on the different building blocks listed above should consider
the recommendations listed by the CIRCASA international consortium on soil carbon sequestration in
Agriculture Soussana et al. (2020). The main recommendations are listed here below:

* A Tiered approach with for Tier 3, verifying systematically SOC change estimates from soil surveys and long-term fields sites, as well as eddy flux covariance.

* A high spatial resolution (ca. 10 m to include small fields and small owners) based on remote sensing.

* A high accuracy target even if a low initial accuracy is expected, but investment needs to attain high accuracy will be estimated each year.

* A three pillar structure: i) SOC pillar (involving soil science community, soil maps and digital soil mapping and remote sensing of surface soil), ii) Vegetation pillar (remote sensing of vegetation, phenology and biomass of cropland/grassland), and iii) Activity pillar (agricultural activities based on statistics or on self-reporting).

* A modular structure, each pillar derives products that are coupled with other pillars products to derive gridded ΔSOC estimates with their associated uncertainties, specifying the activity that caused the changes.

* Ensembles of calibrated models rather than single models should be used when possible, and synergies with other model consortia (e.g., climate change modellers) should be explored.

* A strong data infrastructure providing seamless access by multiple users and using the FAIR principles. It would include options for self-reporting especially for activities currently not reported (e.g., organic fertilisers, and crop residues).

* A gradual implementation, combining proxies at global scale in the first year (e.g., changes in annual duration of vegetation cover in arable systems could be used as a proxy of OC input to soil) and advanced implementation in pilot areas.

* Provision of resources for ground truthing and for calibration data (e.g., calibration of NPP at eddy flux covariance sites, direct measurements of crop residues etc.).

OrCaSa also has the ambition of producing a first prototype of scalable quantification platform building on the
AgriCarbon-EO operational processing chain for Tier 3 and an evolution of the NIVA's algorithms for Tiers 1
and 2 thereby meeting CIRCASA's recommendations. Yet uncertainty remains on the use of remote sensing

<figure><img src="image_144.png" /></figure>

The ORCaSa project has received funding
from the Horizon Europe Programme under
grant agreement n° 101059863.
<figure><img src="image_145.png" /></figure>

for mapping soil surface as it is not clear yet how this information could be used in the monitoring process.
Still, for Tier 3, we aim at using a hybrid modelling approach that should contain the following elements:

* A pre-processing module for 'Data ingestion' allowing the updating of existing data sets through automated downloading of e.g., satellite images, weather forcing, activity data and land use maps. Optical Bottom Of Atmosphere (BOA) reflectance of high-resolution optical satellites would be downloaded, uncompressed and relevant spectral bands would be stacked. The weather data would be stored in time series with the associated correspondence matrix to the high-resolution grid defined by the user (to match with remote sensing data). This would be done for the zone defined by the input land cover.

* Then biophysical variables (e.g., LAI) would be retrieved from the satellite reflectance images by inverting a radiative transfer model (e.g., PROSAIL). LAI estimates would be associated to an uncertainty estimate (e.g., following the BASALT approach described in Wijmer et al. 2023).

* Then some of the vegetation's model parameters would be inverted by assimilating LAI time series using again a Bayesian approach allowing to assess uncertainty on the output variables. Other parameters would be defined based on the land use maps (e.g., different parameters depending on the crop type). In the next step, the quantity of crop residues estimated through the modelled outputs (simulated plant biomass) and the activity data (e.g., are straw exported or not) and data on organic amendments would be used as input in a soil model simulating the dynamics of the SOC pools and the CO2 emissions. Depending on the context of MRV, information on soil properties and SOC (content, stability etc.) to run the soil model/module may be obtained through soil products (e.g., SoilGrids) or in-situ data.

* Finally, a post-processing module would allow the construction of the output products based on the posterior crop model parameter distribution and the soil model. Geo-referenced maps of the variables of interest in each model (i.e., radiative transfer, vegetation and soil model) would be constructed as well as cumulative variables (e.g., net annual CO2 fluxes over one cropping year).

Note that several radiative transfer models, vegetation or soil models could be used in parallel in each modelling step for ensemble approaches and without anticipating too much on the future results of the project, the overall architecture of the processing chain described above could be adapted to other ecosystems like forest and grasslands.

Yet, each ecosystem has its specificities, and some building blocks may have to be specific or implemented in a specific way. For instance, activities or software collecting activity data would differ for different ecosystems and models that would assimilate aboveground biomass estimated from remote sensing would rely on sensors of different wavelength: e.g., LiDAR or L band for forest (Yu and Saatchi 2016), C band (e.g. Sentinel-1) for cropland/grassland (Revill et al. 2013; Fieuzal et al. 2017; Baup et al. 2019). Because of other ecosystems like coastal one or even peatland it probably very challenging or impossible to develop a unique framework. For instance, monitoring SOC stock changes at peatland requires the use of SOC models adapted to organic soils (Premrov et al. 2021) and the assessment of the water table depth that is the main driver of SOC stock changes (Wilson 2016)<fnref n="60" />. Water table depth can be measured in situ but large scale monitoring

<figure><img src="image_146.png" /></figure>

<footnote n="60">⁶⁰ See also: https://www.ucd.ie/auger/t4media/AUGER_FinalReport_June 2021.pdf</footnote>
<figure><img src="image_147.png" /></figure>

ORCaSa
Because soil carbon matters

of SOC at peatland may require the coupling of soil model adapted to organic soils coupled with hydrological modules.

### 4.2.2 Reporting and verification

On both those components of the MRV, the CIRCASA initiative made recommendations for cropland that could be adopted or adapted to the other ecosystems.

For reporting, CIRCASA suggested that it should primarily be through gridded data extraction (e.g., of the modelled outputs) for any spatially defined entity (e.g., a field, a farm, a small region, the sourcing area of an industry, or a given crop type, a country etc.) and any time period (e.g., a year for CAP or offsetting programs to several years or decades for NDCs or offsetting projects). All SOC stock changes estimates should be provided with the same unit (e.g., $g C m^{-2}$ or $CO_{2eq}$ per time period selected) and an uncertainty estimate would be provided (if possible as RMSE) systematically. Uncertainties would be calculated by reference with verification methods, noting however that reference methods are also uncertain. For modelling approaches, we also recommend assessing the sources of uncertainties (e.g., input data) and to apply methods allowing uncertainty propagation as described in section 2.5.

Note that reporting could benefit from new technologies. For instance, collection of activity data for reporting could be done through new mobile phone technologies, online portal (Fritz et al. 2019) or connection to Farm Management Information Systems (FMIS) (Fountas et al. 2015) with APIs. Yet our own recent experience shows that activity data in FMIS may lack of reliability/consistency and may require to be checked by a third party (e.g., an agricultural council).

Concerning the baseline, we recommend an adaptive framework and some guidelines/tools that could allow both the accounting of regional and temporal baselines. The operational processing chain described above, would allow both as it could 1) produce information on several years prior, for instance, of a carbon farming program but also all along its life and 2) because this approach based on remote sensing and hybrid modelling allows to simulate plots/farms that have adopted or not C farming practices in the same region.

For verification, we recommend an approach that would be based on soil re-sampling (surveys, grids, demonstration farms, etc.) and remote sensing.

As suggested by CIRCASA, verification should target a high accuracy estimate of vegetation and SOC stock changes over the full soil profile, with sampling and analytical methods limiting biases in final vs. initial C stock estimates. For instance, using the same sampling protocol and tools, using geo-referenced sampling points, using the same analytical procedure done in a single lab.

The number of replicates of soil and vegetation samples in each site (e.g., field, farm, forested parcel) would be sufficiently high to provide a good accuracy (e.g., see CarboEurope or ICOS soil and vegetation sampling protocol at eddy flux sites). Yet, in order to optimise the cost/accuracy ratio of verification, statistical studies would be required to design optimal initial and final soil sampling campaigns. In this perspective, pluriannual high resolution maps of biomass and SOC stock changes produced by hybrid modelling approaches assimilating remote sensing (e.g., AgriCarbon-EO) could be very useful as they would provide insights of the spatio-temporal dynamics of C stock changes. This information could be used to identify areas that preferentially store/lose C (e.g., because of soil conditions that are more or less favourable to plant

<figure><img src="image_148.png" /></figure>

The ORCaSa project has received funding
from the Horizon Europe Programme under
grant agreement n° 101059863.
<figure><img src="image_149.png" /></figure>

ORCaSa
Because soil carbon matters

development), allowing 1) a wider range of change in SOC stocks to be measured (than with a random
sampling protocol) which is very useful for model's validation/verification, and 2) a sampling scheme more
representative of the mean C stock dynamic of the plot/farm. Such an approach could allow a substantial
reduction in the number of soil samples to be collected in order to detect SOC stock changes and with a more
representative/accurate estimate.

<figure><img src="image_150.png" /></figure>

The ORCaSa project has received funding
from the Horizon Europe Programme under
grant agreement n° 101059863.
<figure><img src="image_151.png" /></figure>
<figure><img src="image_152.png" /></figure>

ORCaSa
Because soil carbon matters

# 5. Conclusions

This review has shown that internationally, there is a wide range of application contexts (e.g., NDCs, CAP, voluntary C market, insetting), ecosystems (e.g., croplands, grasslands, forests, wetlands), frameworks, methodologies and guidelines for monitoring, reporting and verification for SOC (and GHG) changes. Similarly, a wide diversity of tools to assess possible effects of land use/management interventions on SOC stocks and GHG emissions are applied in different parts of the world, by a diverse range of stakeholders.

Considering this diversity, and the overarching societal/political demand for a consistent widely applicable and scalable MRV system, a novel framework for a generic MRV methodology was developed. The framework itself expands on earlier influential work (i.e., CIRCASA and CSU, with international partners) further detailing the individual ‘building blocks’ of each MRV component (i.e., monitoring, reporting and verification). Individual ‘building blocks,’ as comprehensively inventoried and discussed here, in-turn may be combined, or (re)used at different stages of the MRV cycle. We also emphasised the importance of uncertainty assessment throughout the entire MRV chain.

Current MRVs use a diversity of guidelines and approved methodologies. These consider a wide range of procedures to manage, for example, additionality, uncertainty, persistence, baselines, measurement, reporting and verification, and so on. A selection of current MRV guidelines and approved methodologies, as applied to various ecosystems in defined geographies, were characterised according to defined ‘main characteristics’, based on a pre-defined number of classes/options for each characteristic. Subsequent multi-dimensional scaling showed that the considered MRVs are fairly uniformly distributed in the two-dimensional space and that there are no clear clusters or extremes, and some patterns were observed. The assessment, however, was not unambiguous as indicated: in the future, it could be worthwhile to organise stakeholder workshops to jointly refine and possibly extend the list of key characteristics of approved MRV methodologies, while also assigning weights to each characteristic to evaluate the sensitivity of the results of the multidimensional scaling procedure to various choices.

The present review and analyses (Task 4.1 of the ORCaSa project) provide an outlook on the directions Task 4.2 (‘Cookbook for a blueprint of an MRV framework for croplands SOC stock changes’) and Task 4.3 (‘Building an integrative and multi-ecosystem MRV framework for SOC stock changes’) of the ORCaSa project might take. Importantly, such a cookbook should consider decision trees for identification of appropriate calculation approaches (i.e., Tier 1, 2 or 3 type) based on data availability and local conditions. Many hybrid and process-based models, for example, require a high level of specialised knowledge to understand and assess their overall performance and quality. They will need to be accommodated in user-friendly SOC tools.

In addition to the above conclusions, some general observations can be made:

* Adapting or developing new approaches to an MRV methodology applicable in a new country or region is not a simple task. Such procedures must consider local economic, environmental and social factors, including farming systems, soil and climatic conditions, regulations, social norms and values.

* There is a need to decouple SOC sequestration, a longer-term goal mainly aimed at climate change mitigation (and carbon offset markets), from storing (or using) SOC in soil to ensure soil health and food security. This corresponds with the well-known ‘carbon-dilemma’, i.e., placing more value on soil

<figure><img src="image_153.png" /></figure>

The ORCaSa project has received funding
from the Horizon Europe Programme under
grant agreement n° 101059863.
<figure><img src="image_154.png" /></figure>

ORCaSa
Because soil carbon matters

carbon stocks than the value of soil for other ecosystem goods and services, which could have adverse side-effects such as land grabbing.

* Importantly, farmers should be duly represented/organised in (new) sub-national scale MRV systems, which operate at the landscape scale, so as to facilitate their access to voluntary carbon markets and help improve their livelihoods. Carbon pricing itself will be an important economic incentive, in particular for those farmers that have a short-term objective (i.e., timescales for long-term gains in soil C are a challenge for farmers with shorter term horizons).

* A hybrid monitoring approach that combines in-situ measurements with process-based or hybrid- models is likely a better solution than relying on such models alone.

* Additional soil sampling will be needed to improve the accuracy and scalability of the models themselves by benchmarking them with independent and high-quality measurements from soil sampling.

* There is a need for a global soil resources centre to bring together old (i.e., existing) and newly collated soil data in a uniform, harmonised way for the benefit of the international community. Mechanisms should be developed through which data held by private organisations as well as commercial companies can be accessed freely through a federated, global soil information system, using open standards, with the source data themselves remaining with the respective data providers.

* Research has indicated the need for soil monitoring (to at least a meter depth) to accurately capture the total net SOC changes under differing managements systems, as well as equivalent mass based calculation of SOC stock changes.

* There is an emerging discussion regarding the linkage of SOC and landscape carbon stocks with biodiversity in the policy and market domain. This would mean the MRV products in the future should be linked across the biodiversity and carbon, and also consider the provisioning of other ecosystem goods and services, in particular water quantity and quality.

* Although there is a need for a generic global MRV framework, applicable at various scale levels, for SOC change to support improvements in soil carbon management respectively sequestration, currently there may be an imbalance in monitoring and verification developments with a shift towards commercialisation and a lot of theoretical development (models and frameworks) but insufficient field experimentation providing data to support these. "New" studies on farming that reflect the future of farming, e.g., sustainable systems, should be accounted for.

* The demand for carbon offsets will be exacerbated by countries and private companies that want to win the "race to carbon neutrality", while "circumventing" the need to reduce fossil-fuel emissions themselves. Safeguards against "greenwashing" through uncertainty quantification and solid verification by independent suitably experienced and qualified third parties will be essential. However, verifiers may not have the right expertise, and many will not have the modelling experience, pointing at a need for training capacity.

<figure><img src="image_155.png" /></figure>

The ORCaSa project has received funding
from the Horizon Europe Programme under
grant agreement n° 101059863.
<figure><img src="image_156.png" /></figure>

ORCaSa

Because soil carbon matters

<figure><img src="image_157.png" /></figure>
<figure><img src="image_158.png" /></figure>
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ORCaSa
Because soil carbon matters

ACKNOWLEDGEMENTS

The ORCaSa project has received funding from the European Union's Horizon Europe research programme under grant agreement n° 101059863 (https://irc-orcasa.eu/).

We thank Senani Karunaratne (CSIRO), Ahmad Al Bitar (CESBIO), Ainhoa Ihasusta (CESBIO), Edouard Lanckriet (Bioline, MARVIC project), Ben MacDonald (CSIRO), Pascal Jouquet (IRD) and Laurent Thuriès (CIRAD) for their useful suggestions and comments which helped to improve the document.

We specially thank Helaina Black (James Hutton Institute) for her constructive review which helped to improve the document greatly.

We are also grateful for the input from participants of the ORCaSa stakeholder webinar (5 July 2023) and the two preceding 'stock take' webinars (America's and Pacific).

<figure><img src="image_160.png" /></figure>
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ORCaSa
Because soil carbon matters

# APPENDIX - Example of a support MRV protocol

Prior to defining a list of characteristics that should be considered when evaluating/comparing different MRV initiatives and related methodologies we will discuss an example, to illustrate a possible workflow. For this, we will use the GSOC-MRV framework (FAO-GSP 2020). The framework was elaborated and subsequently reviewed by a wide range of international experts; as such, arguably it may be seen as a global standard for the development/application of an MRV system at various scale levels. It consists of a series of step-by-step stages and sub-protocols needed in order to assess SOC changes and GHG emissions/removals by the adoption of sustainable soil management (SSM) practices.

The GSOC-MRV framework comprises six successive stages:

* Stage 1: Applicability conditions, is intended to verify that the project and activities meet the necessary requirements for this methodology to be applicable (considers: scale, eligible and restricted lands, land uses and management practices).

* Stage 2: Define spatial and temporal boundaries for the project.

* Stage 3: Define baseline (business-as-usual) and projected intervention scenarios and practices. Includes defining indicator historic and projected relevant activity data for the different areas to be assessed (e.g., areas, crops, yields, tillage practices, fertiliser use, organic amendment use, livestock density).

* Stage 4: Preliminary assessment of the additionality of the projected practices (i.e., assess how much carbon would be sequestered in soils and how much GHG emissions will be reduced, compared to a situation in which the proposed technologies or changes would not have existed).

* Stage 5: Monitoring is implemented to monitor effects of implemented practices (can include field sampling as well as modelling).

* Stage 6: Reporting and verification. In the FAO protocol, following up on the pre-implementation report, bi-annual reports are made describing performed activities, soil sampling results and modelling estimates. Verification of results/projections should be done by an independent party; as such, it seems desirable to define "verification" as a separate stage (e.g., stage 7).

As shown in Figure 8, the successive steps can be subdivided into a 'pre-SSM implementation phase (includes stages 1 to 3), 'SSM-implementation' phase (includes stages 4 and 5), and 'Reporting a verification' phase (stage 6 resp. 7). Appropriate methodologies and protocols that may be used during the successive stages of monitoring are succinctly described in the GSOC-MRV report. The framework also includes suggestions and guidelines concerning the various responsibilities of parties when implementing the MRV framework.

<figure><img src="image_162.png" /></figure>
<figure><img src="image_163.png" /></figure>

ORCaSa
Because soil carbon matters

<figure><img src="image_164.png" /><figcaption>Figure 8 Example of support MRV protocol (Credit: FAO-GSP 2020).</figcaption></figure>

<figure><img src="image_165.png" /></figure>

The ORCaSa project has received funding
from the Horizon Europe Programme under
grant agreement n° 101059863.
<figure><img src="image_166.png" /></figure>

# GLOSSARY

Source: This list of terms has been derived from various sources<fnref n="61" />.

**Additionality:** A demonstration that carbon sequestration and/or reductions in GHG emission associated with the adoption of new land management practices would be greater than the 'business as usual' scenario and would not happen without incentives from the carbon markets. (This is one of four factors to consider when acquiring carbon offsets, i.e., a core provision for environmental integrity in carbon markets.)

**Abatement:** Refers to reducing the amount of GHG emissions released to the atmosphere (from soil) and/or increased amounts of (soil) carbon sequestered in the environment via the removal of GHGs already in the atmosphere.

**Article 6:** The cooperation mechanisms enshrined in Article 6 of the Paris Agreement offer Parties the opportunity to cooperate with one another when implementing their nationally determined contributions (NDCs).

**Baseline:** A baseline scenario assumes the continuation of pre-project conditions, including agricultural management practices. This forms the reference point for determining the outcomes from a soil carbon project with the use of MRV. For soil carbon projects, baselines may be dynamic or fixed. The former will be updated throughout a project while the latter will reflect conditions prior to the start of a project.

**Baseline scenario:** The most likely scenario in the absence of the crediting mechanism, including all assumptions on drivers for relevant emission reductions.

**Building blocks** (of MRV framework): One of the separate parts that combine to make the MRV. For example, databases (e.g., soil, management, plant models, soil SOC/GHG models, remote sensing). Building blocks can be assembled in an operational processing chain to be applied in one or several contexts of applications (e.g., CAP, Carbon market, NDC). Note that the same building blocks can be used in one or several components of an MRV (e.g., M or R, see Figure 4 in report itself). [Source: ORCASA](https://www.orcasa.eu/en/consultation-with-the-eu-marvic-s-evolving-glossary-of-definitions); **Cap and trade:** A regulatory procedure that puts a 'cap' on the amount of greenhouse gas emissions that companies are permitted to emit. Firms that come in under their limitations have the option to 'trade' (sell) their excess emission permits to other companies that have exceeded their limit.

**Carbon brokers:** An individual or company that work with buyers and sellers of carbon credits to facilitate carbon trading. This can be driven by buyers looking to source offsets, or matching creators of carbon credits

<figure><img src="image_167.png" /></figure>

<footnote n="61">⁶¹ This glossary is provided for 'general information.' It is not necessarily authoritative on all terms listed. For example, recent EU-Projects such as MARVIC are specifically focussing on developing a standard "glossary of definitions for the EU MRV Framework for carbon farming." The main sources consulted here are: [https://irc-orcasa.eu/](https://irc-orcasa.eu/) (in consultation with the EU MARVIC's evolving 'Glossary of definitions'); [https://carboncredits.com/carbon-credits-glossary/](https://carboncredits.com/carbon-credits-glossary/); and, [https://apps.ipcc.ch/glossary/](https://apps.ipcc.ch/glossary/).</footnote>
with a market. Brokers are not themselves regulated, so buyers and sellers should exercise due diligence
before engaging with a broker.

**Carbon credit:** The unit that is certified by a carbon credit programme or standard for trade in carbon markets, representing one metric tonne of carbon dioxide equivalent. Verifiable soil carbon credits will be determined through the relevant quantification approach and MRV methods.

**Carbon dioxide equivalent:** A metric, often written as CO2eq, used to compare GHGs on the basis of their global warming potential, by converting amounts of other gases, usually nitrous oxide and methane, to the equivalent global warming potential of carbon dioxide. Note that the shorter life span of methane means that the calculation should be done on a 20-year rather than 100-year basis for this gas.

**Carbon farming (CF):** The management of carbon and GHG fluxes, with the purpose of mitigating climate change. This involves the management of both land and livestock, all carbon pools in soils, vegetation and harvested products, plus fluxes of CO2 and CH4, as well as N2O. The outcome of CF can be: 1) carbon removals, 2) avoided emissions, 3) reduced emissions, or a combination of them. [Source: ORCASA]

**Carbon farming scheme (CF scheme):** Governance system regulating a set of CF projects and the monetisation of their outcomes. A CF scheme consists of guiding principles, rules and methodologies for monitoring, reporting and verification (MRV). Synonyms : carbon (payment) programme, carbon standard.
[Source: ORCASA].

Carbon farming programme, Guiding principles :

1) *Additionality*: implies that the generated emission reductions and/or carbon removals would not have occurred under the 'business-as-usual' scenario (i.e., without the carbon finance or incentive)

2) *Permanence*: indicates the sustained climate mitigation effect in the long-term

3) *Double counting*: appears when a climate benefit (a quantity of CO2eq) is reported twice (or more) either by two different actors into the same sector, or by one (or more) actors in another sector

4) *Carbon leakage*: the (unintended) spatial shift of GHG emissions and/or the shift in GHG emissions within or outside the spatial scope of the CF project due to trade-offs (e.g., due to emissions in other carbon pools or emission types) caused by the implementation of CF practices ; and,

5) *Management of uncertainties and risks (U&R)* — Procedures and buffers adopted to cope with U&R to guarantee that climate benefits have not been overestimated due to uncertainty in the monitoring method (calculation U&R) or by unexpected or accidental human or natural disturbances (project U&R). [Source: ORCASA].

**Carbon farming, rules for:** Basic agreements for establishing and implementing CF projects, such as the guiding principles and the processes from project plan to certification.

**Carbon inset(ting):** A broad term to describe emission reductions or removals achieved within the supply chain of an entity that are used to compensate for entity emissions; a carbon credit secured through investment within the supply chain of an entity. Aimed at offsetting a company's emissions or environmental and social impacts, within the supply chain.

**Carbon finance:** Finance that intends to reduce the impact of greenhouse gas emissions. The term can refer to the concept or methodology of channelling finance towards emissions reducing activities, or the flow of finance or investments themselves.

<figure><img src="image_168.png" /></figure>
<figure><img src="image_169.png" /></figure>

**Carbon market:** A market in which units — allowances or credits — are traded between entities. When units are used for voluntary purposes or where carbon credits are certified solely by voluntary programs or standards, the market is often referred to as a 'voluntary' carbon market (VCM). Where units are used to satisfy legal compliance obligations, this is often referred to as a 'compliance' market.

**Carbon neutrality:** Worldwide equilibrium between anthropogenic emissions and anthropogenic absorption. As such, an organisation, product, or service cannot be carbon neutral by itself but can contribute to achieving global carbon neutrality. The objective of carbon neutrality is twofold: to reduce the total amount of emissions and increase absorption capacity.

**Carbon offset(ting):** The use of carbon credits, or other units, to compensate for a country's or company's emissions covered by a compliance or voluntary target. Often used when the carbon credit is generated outside of a country or company supply chain to compensate for the country's or company's emissions.

**Carbon offset standards:** Recognised standards, protocols or/and methodologies to guide GHG quantification, monitoring and reporting.

**Carbon registry:** Independent authority that approves, lists, and tracks a carbon credit's ownership. See for example the American Carbon Registry (ACR), EU Emissions trading Register (EU-ETS) and VERRA.

**Carbon sequestration:** The removal of carbon dioxide from the atmosphere and storage in another system, such as soil or vegetation. If the carbon dioxide sequestered is more than the carbon dioxide emitted, the store is increasing and is known as a carbon sink.

**Carbon sink:** A forest, ocean, land, or soil that absorbs more carbon dioxide than it emits.

**Carbon stock:** The absolute mass of carbon in a (soil) sample of known volume — typically expressed in tonnes per hectare to a specific depth, or preferably and equivalent mass basis (see Wendt and Hauser (2013)).

**Carbon trading:** A market used to manage greenhouse gas emissions; instead of cutting their own emissions to meet mandatory targets, companies can pay someone else to cut theirs, or to sequester carbon.

**Certification (of carbon credits):** Voluntary emission reduction (VER) are carbon credits issued by a verified project. Standards such as VCS or the Gold Standard follow a rigorous methodology to certify the projects and their carbon credits. For a project to be certified, it has to be **real** (proven to have taken place), **measurable** (all emission reductions/removals have to be quantifiable using recognised measurement tools, with uncertainty and leakage taken into account, against a credible emission baseline), **permanent** (in the case of a risk of reversibility, adequate safeguards need to be implemented), **additional** (see above), **independently verified** (by an independent qualified third party) and **unique** (no more than one carbon credit can be associated with a single emission reduction or removal as one metric ton of carbon dioxide equivalent (CO2eq)). [Source: SBTI].

**Climate contribution:** Supporting an emission reduction project in the Voluntary Carbon Market that not only captures or avoids greenhouse gas emissions but also contributes to the United Nations Sustainable Development Goals. Climate contribution is different from carbon offsetting as there is no definite point of arrival: the more contribution and emission reduction, the more benefits for the planet.

**Co-benefits:** Additional positive externalities of carbon reduction project, which target the United Nations Sustainable Development Goals (UN SDGs).

<figure><img src="image_170.png" /></figure>
<figure><img src="image_171.png" /></figure>

ORCaSa
Because soil carbon matters

**Code:** The GHG accounting rules that determine project eligibility, additionality, and baseline and project emissions for a particular project type. The code also includes the program requirements for monitoring, reporting, verification, and certification. The terms code, protocol, and methodology are often used interchangeably (which can be confusing).

**Compliance markets:** Also known as *mandatory markets*, are governed by national, regional, or provincial law and compel emission sources to meet legally mandated GHG emissions reduction targets. Because compliance programmes offset credits are generated and traded for regulatory compliance they typically act like, and are priced like, other commodities.

**Crediting period:** The period over which credits can be generated for a project, typically between 7 and 25 years. For some codes, a crediting period can be renewed at the end of the term.

**Double counting:** Term describing the situation in which two parties claim the same carbon removals or emission reductions.

**Ecosystem services:** The diverse range of services that we derive from the natural environment. Four categories of ecosystem service have been identified: Provisioning, Regulating, Cultural, and Supporting.

**EU farming initiative:** There are four key elements in the EU carbon farming initiative: adopting a common standard for *Monitoring, reporting, and verification*; a regulatory *Framework for certifications on carbon removals*; *Knowledge transfer to farmers*; and, access to *Funding options*.

**Global warming potential (GWP):** The global warming potential of a gas refers to the total contribution to global warming over a defined time frame resulting from the emission of one unit of that gas relative to one unit of the reference gas, carbon dioxide, which is assigned a value of one.

**Gold Standard Verified Carbon Standard (GS VER):** A non-governmental emission reductions project certification scheme. It participates in the Clean Development Mechanism (CDM), the Voluntary Carbon Market, and many climate and development initiatives.

**Greenhouse gases (GHG):** Gases that trap heat in the atmosphere. Carbon dioxide ($CO_2$), methane ($CH_4$), nitrous oxide ($N_2O$), and fluorinated gases are the primary greenhouse gases. See also: Carbon Dioxide Equivalent.

**Greenwashing:** A behaviour or some activities that make people believe that a company is doing more to protect the environment than it really is (see *here* for examples).

**Guidelines:** A practical translation of the MRV framework [Source: ORCASAS].

**Insetting:** See carbon insetting.

**ISO 14064-1:2018:** Standard that specifies principles and requirements at the organisation level for the quantification and reporting of greenhouse gas (GHG) emissions and removals. It includes requirements for the design, development, management, reporting and verification of an organisation's GHG inventory. The ISO 14064 series is GHG programme neutral. If a GHG programme is applicable, requirements of that GHG programme are additional to the requirements of the *ISO 14064* series.

**Leakage:** Leakage is used to account for increased GHG emissions or losses in carbon sequestration beyond a project boundary which have occurred as a result of the project. For example, lower productivity or intensification of land use or management elsewhere.

<figure><img src="image_172.png" /></figure>

The ORCaSa project has received funding
from the Horizon Europe Programme under
grant agreement n° 101059863.
<figure><img src="image_173.png" /></figure>

ORCaSa
Because soil carbon matters

**Mandatory market:** Synonym for compliance market.

**Monitoring** (M in Figure 4): Process of quantifying the net climate mitigation impact of a CF project, including all necessary steps from establishing a baseline (or business-as-usual scenario), to comparing this baseline to a project scenario (e.g., through measurements or modelling). [Source: ORCASA and MARVIC].

**MRV:** Monitoring, Reporting and Verification (MRV) is a key component of all carbon projects. Information from a carbon project is monitored and reported on a regular basis throughout the crediting and permanence periods. A verification stage then validates that a project has performed as predicted and that anticipated carbon outcomes have been realised, based on the reporting.

**MRV framework:** Set of guiding principles and rules for implementing CF and forest projects, and definition of methodologies for monitoring, reporting and verification (MRV) of carbon farming projects. For instance, it will define:

* the duration of the projects

* the boundaries of the projects: scale (e.g., parcel/farm level) and Land Use considered for projects

* which type of forest project (e.g., afforestation, protection) or CF practices are accounted for (e.g., will it consider biochar, reduction in mineral fertilisers)

* how is the baseline defined: *regional baseline* (e.g., considering the management practices/cropping or forest systems usually implemented in the region surrounding the farm) or *local baseline* (e.g., considering the management/cropping system of the previous 3 years before stating the CF project)

* the monitoring methods that can be used for calculating C storage and avoided/reduced emissions.

* depth of the soil to be considered for assessing SOC stock changes, and,

* discount depending on the accuracy of the monitoring method. [Source: ORCASA]

**MRV method:** Guidance and requirements for MRV are generally stipulated in an MRV Method or Protocol document approved and issued by a carbon programme organisation. Specific MRV approaches for a soil carbon project will reflect their application of this MRV document to the project's circumstance.

**MRV templates:** MRV templates are forms that go with specific guidelines and need to be filled in. [Source: ORCASA]

**Nationally Determined Contributions (NDCs):** Countries' self-defined national climate pledges under the Paris Agreement, detailing what they will do to help meet the global goal to pursue 1.5°C, adapt to climate impacts and ensure sufficient finance to support these efforts.

**Nature-based solutions:** These solutions involve working with nature to address societal challenges, providing benefits for both human well-being and biodiversity. Specifically, they are actions that involve the protection, restoration, or management of natural and semi-natural ecosystems; the sustainable management of aquatic systems and working lands, such as croplands or timberlands; or the creation of novel ecosystems in and around cities. They are actions that underpin biodiversity and are designed and implemented with the full engagement and consent of local communities and Indigenous Peoples.

**Net negative:** Tonnes of GHGs avoided, reduced or removed that exceed the unabated GHG emissions.

<figure><img src="image_174.png" /></figure>
<figure><img src="image_175.png" /></figure>

ORCaSa
Because soil carbon matters

**Net zero:** A means to reach global carbon neutrality. Net zero corresponds to a situation where the amount of an organisation's greenhouse gas emitted is equal to the amount of greenhouse gas captured or removed from the atmosphere (see also Greenwashing).

**Offsetting:** See Carbon offsetting

**Offset certificates:** Paper licences provided in exchange for the purchase of carbon credits. Offset certificates should include a serial number unique to the offset, total tonnage bought, the verifier's name and signature, project location, owner's name and address, and a vintage date.

**Paris Agreement:** An international treaty on climate change that superseded the 1997 Kyoto Protocol. Signed in 2016, the agreement has been ratified by all but six countries in the world. The long-term goal of the Paris Agreement is to keep global warming below 2°C, and preferably limiting the increase to 1.5°C, and the treaty contains various provisions to enforce this target.

**Permanence:** A necessary condition for carbon projects to demonstrate that carbon credits reflect a long-term removal of GHGs. For soil carbon projects, this generally means the continuance of the positive carbon management practices to ensure that there are no reversals.

**Permanent offsets:** Offsets that are long-lasting or guaranteed to be replaced in the event of a loss. This is one of four factors to consider when acquiring carbon offsets.

**Permanence period:** The defined time period that sequestered C must remain sequestered during the period of the offset credits. The permanence period is individually defined by each code and can vary from one code to another.

**Project area:** The project area is the physical spatial area or areas submitted for certification. It contains the area required to successfully manage the explicit objectives of the project.

**Project boundary:** The clearly defined physical boundary or edges of the project that delineate the Project Area from non-Project Areas.

**Project scenario:** The Project Scenario is defined as the scenario that will exist once the Project is implemented and operational.

**Protocols:** Describe how a methodology should be implemented (e.g., how to measure SOC or biomass in the field, sample soils, or how to simulate the baseline and the stock change). [Source: ORCASA]

**Real Offsets:** Carbon offsets that have already actually reduced carbon emissions, as opposed to those that are expected to do so in the future.

**Registry:** Programme registries are the platforms which enable the trading of carbon credits. A registry facilitates the transparent listing of information on registered carbon projects including issued and retired carbon credits units.

**Reporting** (R in Figure 4): Process of communicating the monitored results/activity data (farmer's data, earth observation (EO), between project developers (farmer, cooperatives...) and the owners of a CF scheme (e.g., Ministry of Environment for the Label Bas Carbone). Reporting typically details project results, or progress and impact, based on a standardised communication process and a standardised set of proofs and data (generated from the monitoring methods). Reporting can include the flow of data towards a registry [Source: ORCASA and MARVIC].

<figure><img src="image_176.png" /></figure>

The ORCaSa project has received funding
from the Horizon Europe Programme under
grant agreement n° 101059863.
<figure><img src="image_177.png" /></figure>

ORCaSa
Because soil carbon matters

**Regulated carbon market:** Market where members are legally obligated to reduce their emissions.

**Requirements:** Elements (rules, procedures, guidelines) that the activity must conform to in order to proceed through Validation/Verification and ultimately Certification.

**Retire:** To permanently remove carbon offsets from the market in order to prevent them from being resold after they have been used up. Offsets are typically decommissioned by assigning them unique serial numbers and registering them in an official registry.

**Reversal:** Reversals are a component of permanence and used to account for losses from a project's net sequestered carbon. Reversals can be intentional (e.g., ploughing) or unintentional (e.g., extreme weather).

**Rules for carbon farming:** Basic agreements for establishing and implementing CF projects, such as the guiding principles and the processes from project plan to certification (see also **Carbon farming, rules for**). [Source: ORCaSa].

**Soil inorganic carbon (SIC):** The amount of (mineral forms of) carbon in soil held in carbonates.

**Soil organic carbon (SOC):** The amount of organic carbon stored in organic matter in the soil. It comes from decomposing plant material and is vital for soil health. About 58% of soil organic matter is carbon.

**Tier levels:** A tier represents a level of methodological complexity (in the 2006 IPCC Guidelines). Usually, three tiers are provided. Tier 1 is the basic method (based on IPCC default values), Tier 2 intermediate (allows for location-specific coefficients) and Tier 3 (uses mechanistic SOC and biogeochemical models) the most demanding in terms of complexity and data requirements. Tiers 2 and 3 are sometimes referred to as higher tier methods and are generally considered to be more accurate on condition that adequate data are available to develop, evaluate and apply a higher tier method (IPCC 2019c).

**Validation:** An independent process for the evaluation of a carbon project plan to establish that the project should achieve the predicted carbon abatement and meets relevant eligibility and other programme criteria.

**Verifiable offsets:** Carbon offsets that can be quantified, tracked, and validated are known as verifiable offsets. (This is one of four factors to consider when acquiring carbon offsets.)

**Verification (V in Figure 4):** Ability of (independent) external parties to check the truthfulness and accuracy of project outcomes (e.g., soil analysis to measure SOC stock changes, remote sensing to verify that a practice was implemented (or not)). A proper verification ensures that the project is implemented according to its proposed rules (e.g., was the baseline correctly defined), methodology, and guiding principles. Hence, an authorised third-party auditor must also conduct an impartial review of the carbon offset project design and baseline calculations prior to the start of project activity. [Source: ORCASA and MARVIC].

**Verifier:** An accredited (reputable, competent) and independent person or persons with responsibility for performing and reporting on the verification process.

**Verra:** One of the main carbon credit registries for voluntary carbon credits (alongside The **Gold Standard**). Verra is a non-profit and the first organisation to create an internationally recognised methodology to provide quality assurance to voluntary carbon markets.

**Voluntary Carbon Market (VCM):** A carbon market in which members are not legally compelled to reduce their emissions but do so voluntarily. These markets enable carbon emitters to offset their emissions by acquiring carbon credits generated by third-party initiatives aimed at removing or decreasing GHG emissions

<figure><img src="image_178.png" /></figure>
<figure><img src="image_179.png" /></figure>

ORCaSa
Because soil carbon matters

from the environment. Companies can engage in the voluntary carbon market on their own or as part of an industry-wide programme.

<figure><img src="image_180.png" /></figure>

The ORCaSa project has received funding
from the Horizon Europe Programme under
grant agreement n° 101059863.
<figure><img src="image_181.png" /></figure>
<figure><img src="image_182.png" /></figure>

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ORCaSa
Because soil carbon matters

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The ORCaSa project has received funding
from the Horizon Europe Programme under
grant agreement n° 101059863.
<figure><img src="image_186.png" /></figure>

ORCaSa
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grant agreement n° 101059863.
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ORCaSa
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<figure><img src="image_195.png" /></figure>

The ORCaSa project has received funding
from the Horizon Europe Programme under
grant agreement n° 101059863.
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ORCaSa
Because soil carbon matters

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ORCaSa
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The ORCaSa project has received funding
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ORCaSa
Because soil carbon matters

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The ORCaSa project has received funding
from the Horizon Europe Programme under
grant agreement n° 101059863.
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ORCaSa
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<figure><img src="image_219.png" /></figure>

The ORCaSa project has received funding
from the Horizon Europe Programme under
grant agreement n° 101059863.
<figure><img src="image_220.png" /></figure>

ORCaSa
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<figure><img src="image_221.png" /></figure>

The ORCaSa project has received funding
from the Horizon Europe Programme under
grant agreement n° 101059863.
<figure><img src="image_222.png" /></figure>

ORCaSa
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The ORCaSa project has received funding
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ORCaSa
Because soil carbon matters

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<figure><img src="image_237.png" /></figure>

The ORCaSa project has received funding
from the Horizon Europe Programme under
grant agreement n° 101059863.
<figure><img src="image_238.png" /></figure>

ORCaSa
Because soil carbon matters

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The ORCaSa project has received funding
from the Horizon Europe Programme under
grant agreement n° 101059863.