On the 30th of July, BeZero Carbon hosted a webinar on the risks for Afforestation, Reforestation & Restoration projects, the first in a new series for developers on how we view risks among projects in each sub-sector. The session featured a short Q&A. We’ve shared our responses to the questions below.
Key takeaways
This webinar provided a technical exploration of our approach, including higher and lower risk examples to contextualise our perspective.
It also gave insight into how our geospatial and earth observation capabilities feed into our assessments.
We received lots of questions from the audience which our team of experts has answered below.
Q&A
Q: What are you seeing in terms of projects that are combining native and commercial species?
A: There are scenarios where native species and commercial species are the same thing, however we will answer regarding mixing native and non-native species. There are a few distinct ways in which projects can incorporate native and non-native species. Firstly, there are projects that plant mixed native and non-native species in individual stands for mixed outcomes, for example one area of potential is the interplanting of non-native commercial species within native regeneration to aid in offsetting the costs of natural regeneration. Secondly, there are projects that have distinct parcels that conduct different activities that may mix native and non-native species within each parcel or between parcels. These often include agroforestry, woodlots, and horticulture, the choice of which is tailored to the landholder’s needs. Thirdly, there are projects that conduct non-native commercial ARR using non-native species alongside activities in other sub-sectors, such as Avoided Deforestation or Improved Forest Management of native species.
Q: I’m interested in general methods used to rate ARR projects, and in particular how your methods might apply at smaller scales. At what size/scope does a project reach or exceed a practical rating level?
A: BeZero Carbon is able to apply our assessment to any size of project, provided there is sufficient data provided to conduct our assessment. For example, we have rated a 40-hectare project in Scotland, as well as many distributed community-based projects, wherein parcel sizes can be well below one hectare.
Depending on planting patterns, it can sometimes be difficult to assess small-scale projects using remote sensing due to the resolution of available datasets, especially for older projects. In these cases - acknowledging the limitations of geospatial and remote sensing - we use the data provided by the project, which is verified by a third party, and literature sources.
Q: How does BeZero think about buffer swaps? How are they treated and weighted in the rating methodology? Do they have negative/positive/no impact on the outcome?
A: The contribution of buffer pool credits from another project may introduce risk that the swapped credits are from projects with a lower carbon efficacy than the rated project, and therefore not appropriate to cover any potential loss event that may occur. This risk may be heightened where projects or registries do not disclose which other projects these buffer pool credits originate from. This potential risk is captured in our assessments of non-permanence and information risk.
Q: Does BeZero take into account the market for the type of wood produced when pruning and thinning? Do you analyse the market risk of the project?
A: This question most readily applies to our assessment of commercial forestry projects. In these cases, we do consider whether the project has access to infrastructure for processing and distributing products. This applies to pruning, thinning and final harvest. This is analysed as part of our additionality, carbon accounting, and non-permanence risk factors. In additionality, this is considered under potential barriers to projects activities. In carbon accounting we assess the impacts on harvested wood pools and leakage risks, for example if firewood was being obtained from shrublands pre-project and has potential to still be produced from the project area. In non-permanence, access to processing infrastructure plays a role when it impacts carbon in a harvested wood products pool. In an ex ante rating, this would also play a part in our assessment of a project’s execution risk, as access to markets is key for project success.
Q: In additionality, there are ARR projects that can become additional because they provide more benefits than the plantations proposed as business as usual. Are these co-benefits taken into consideration?
A: The BeZero Carbon Rating is an assessment of the carbon efficacy of credits and thus is not an assessment of a project’s co-benefits or SDG claims. In some cases, these aspects will be considered in relation to our assessment of carbon efficacy where relevant to the risk factor in question. For example, permanence can be affected by how effectively the project is benefiting the community and whether the community supports the project. Alternatively, how projects engage and recompense communities for forgone activities can inform our assessment of leakage. We discuss this in greater detail in the ARR methodology on pages 54-57.
BeZero provides insight to the non-carbon impacts of projects via several product offerings. BeZero considers two primary factors when considering its beyond carbon assessment: negative impact risk and positive impact likelihood. BeZero considers negative impact risk through the safeguards a project has in place. Positive impact risk is informed by a project’s SDG contributions. This can include an analysis of the robustness of the SDG impact metrics, the method the developer used to measure the SDG contributions, and the quality and durability of the impacts reported.
We offer the BeZero ‘Beyond Carbon’ dashboards for each ex post rated project. The dashboard allows users to compare the SDGs claimed across projects. The dashboard also includes an SDG Certification Score, the results of an analysis of the requirements the project had to meet through its methodology to make SDG claims. This can indicate the robustness of SDG impact data provided for by the project.
We are currently exploring adding information on co-benefits (e.g., biodiversity) & the safeguards associated with specific ex post projects. This can help indicate the risk of negative impacts the project could have on local people and the environment.
BeZero also offers bespoke beyond carbon assessments which can be tailored to the client’s needs. A complete beyond carbon impact assessment would include both analysis of the negative impact risk and positive impact likelihood. However, clients can request the independent analysis of either the negative or positive impact factor.
Q: How does BeZero Carbon assess agroforestry projects in Europe?
A: Independent of sector group or geographic location, our project assessments always focus on three key risk factors: additionality, carbon accounting, and non-permanence. Agroforestry projects present unique challenges regarding the monitoring of project activities and whether or not they are common practice due to the need to differentiate project-related tree planting from other crops and existing trees within the project boundaries.
We combine a range of datasets to evaluate evolving tree cover and biomass stocks inside and outside the project area. In particular, we use Planet’s 3-metre resolution monitoring product, which provides estimates of canopy height, canopy cover, and aboveground carbon density on a quarterly basis, enabling the monitoring of individual trees. In addition, we use a range of moderate resolution products, like our 10-metre resolution in-house canopy cover model, Planet’s 30-metre resolution Forest Carbon Diligence product, and public datasets like spaceborne LiDAR from GEDI and the Global Forest Change dataset. We also make extensive use of forest inventory data, for example to assess species specific growth rates in a particular area. In Europe, datasets are generally better documented, providing more reliable data. When needed, we validate the presence of trees by direct inspection of high resolution imagery. Ultimately, we find that the above mentioned datasets complement each other, and the precise assessment therefore depends on the project location, activities, and start date.
Q: How are you approaching dynamic baselines for ARR projects?
A: We have implemented dynamic baselines for Avoided Deforestation projects, and have recently extended this approach to Improved Forest Management and ARR projects. Such baselines help us determine the likelihood of afforestation and reforestation activities to occur without the project’s intervention. A variety of factors are taken into consideration to select the most representative control pixels, such as environmental conditions, land ownership and management inside and outside the project area, and precise project activities. For example, commercial forestry can be common practice on a given landscape, but planting of native species or restoration of natural forests may have greater dependence on carbon finance.
For the ARR subsector, we evaluate the carbon stocks, and patterns of planting and clearing using a range of remotely sensed products and field inventory data. For example, we use Planet’s estimates of forest biomass, tree height, and canopy cover, with spatial resolutions ranging from 3 m to 30 m, depending on the year. We also incorporate information from airborne and spaceborne LiDAR and forest inventory plots, where available, to evaluate the uncertainty of remotely sensed data and inform our baselines of carbon stocks and change.
Q: What kind of remote sensing tools can be used to analyse sensitive data in areas with common land use problems such as in areas in Brazil?
A: Understanding land ownership and conflicts is crucial for the assessment of risk to nature-based projects, including Afforestation, Reforestation & Restoration (ARR) projects. This involves examining a range of public and private geospatial datasets on protected areas, indigenous territories, community lands, and settlement areas, to verify land ownership rights. This also includes an evaluation of current and historic land management that could impact the land tenure or threaten the carbon stocks, including an assessment of remotely sensed data.
Illegal deforestation by local communities living in or near project areas is a significant issue in countries such as Brazil, though it is generally of lesser concern in ARR projects, where the baseline often involves unproductive or degraded lands. However, the presence of existing vegetation in the project area, such as details on species, height, and canopy cover, is crucial when assessing additionality and preventing over-crediting. It's also important to determine whether any vegetation has been removed to plant new trees, as this impacts the project's baseline.
Understanding these factors helps us identify the initial drivers of land loss, such as shifting cultivation or grazing. Local communities, often dependent on subsistence farming or small-scale agriculture, may clear forests for crops or pasture land or collection of fuel wood, which can undermine the goals of ARR projects to restore and enhance forest cover. Therefore, ongoing pressures from local communities must be carefully managed to maintain the environmental integrity of these projects. Furthermore, varying claims to land can result in land disputes which can impact the permanence of an ARR project.
At BeZero, we combine a range of remotely sensed forest monitoring products to evaluate historic vegetation conditions and land management. Our partnership with Planet Labs and Kayrros provides access to their forestry products, providing insights into canopy cover, height and aboveground biomass at moderate (10-30 m) to high (3 m) spatial resolution. Public datasets like Global Forest Change provide long-term records of forest loss (since 2000) based on Landsat, while the recent launch of spaceborne LiDAR instruments offer detailed information on forest structure, aiding in the assessment and monitoring of biomass, tree heights, and canopy cover. Each of these datasets provides unique information, for example on pre-existing vegetation density and structure or small-scale clearing of forest. We combine these data with a range of contextual information from literature and project documentation, to understand land ownership and use by the developer and nearby communities and how these may affect different risk factors.
For a detailed case study on the importance of land tenure in understanding risks in Brazil's voluntary carbon market, you can refer to the link here.
Q: How do remote sensing and global geospatial datasets support and improve the development of ARR projects?
A: Geospatial and Earth observation data are used (along with other criteria covered in the ARR webinar) to inform our view on additionality, carbon accounting, and non-permanence.
Developing an Afforestation, Reforestation, and Revegetation (ARR) carbon project involves several steps where remote sensing can play a crucial role. During project site selection, moderate resolution satellite imagery from the Landsat (30 m) and Sentinel-2 (10 m) can be used to analyse current and historic land cover and use. Spaceborne LiDAR and other datasets on forest height and structure, like the Planet Forest Carbon Diligence dataset, provide further evidence of the historic vegetation present at individual land parcels, critical for determining eligibility and making adequate deductions for any vegetation cleared. Topographic or digital elevation models (DEMs) are essential for understanding terrain and identifying suitable planting areas.
Satellite monitoring and other existing geospatial datasets are also an effective tool to establish the project’s baseline, for example if the project activities are common practice, which often requires an assessment of the larger landscape or geographic region. Public datasets such as the Spatial Database of Planted Trees (SDPT) and Global Forest Change product complement commercial datasets such as those from Planet and Kayrros to provide spatially explicit estimates of planted trees in the region, while databases like those from the FAO offer national insights. Some methodologies, like Verra’s VM0047, allow for the use of remotely sensed data to establish the baseline, for example, to determine the stocking index using vegetation indices and monitoring of forest attributes retrieved from satellite observations, such as canopy cover.
Satellite monitoring can also help with carbon accounting and the assessment of non-permanence risks. For example, local or regional forest inventory data can be combined with LiDAR and optical data to monitor forest extent, height, and carbon stocks. At BeZero we combine a range of public and commercial (e.g. Planet and Kayrros) datasets with forest inventory data to evaluate carbon stocks and change. Coarse resolution (>100 m) satellite sensors, like MODIS and VIIRS, are ideal for monitoring natural risks such as fire, drought, and cyclones, due to their daily global coverage and long time-series. Our risk assessments also use many derived data, like climate data from ECMWF for drought monitoring or the IBTrACS datasets of tropical cyclones.
BeZero Carbon’s ex ante ratings and reports offer a comprehensive assessment of carbon project quality by evaluating key factors such as additionality, permanence, leakage, and co-benefits. This innovative approach provides transparency and insight into the potential future performance of carbon projects, helping investors and stakeholders make informed decisions. For more details on the BeZero Carbon ex ante Rating, please see here.
Q: How do you evaluate the baseline when the ecosystem of the region differs from a forest, especially when land cover is challenging to assess for degradation or quantification of GHG using satellite images?
A: Evaluating baselines in ecosystems other than forests or in open forest types can be challenging based on satellite monitoring alone. Our team has a deep understanding of satellite monitoring and limitations related to sensor characteristics or modelling approaches. To overcome these challenges, we use a range of public and commercial datasets, alongside our in-house forest modelling approaches that each complement each other. For example, the Global Forest Change dataset provides a global long-term record of forest loss, but may not perform well regionally or may not identify open canopy ecosystems as forests. In such cases we can use a combination of Planet (canopy cover fraction), our in-house model trained against regional reference data, and spaceborne LiDAR to assess forest extent and loss. We combine a large global dataset of forest inventory data and high-resolution satellite imagery to evaluate the quality of remotely sensed data products used and provide further insights on expected carbon stocks and growth rates.
Satellite monitoring is just one aspect of BeZero’s analyses. For example, to evaluate the baseline we would also consider evidence provided in the project documentation and relevant scientific literature.
Q: What are the main criteria to rate a project and how manage the particularities of each project in this rating?
A: The assessment of a carbon credit’s efficacy includes a detailed, project-specific, bottom-up, and top-down analysis, to provide a comprehensive assessment of risk. To make our assessment, BeZero Carbon analysts use a broad range of qualitative and quantitative inputs including, but not limited to, financial, environmental, and policy assessment techniques based on primary and secondary data sources. In order for a project to be eligible for a rating, it must meet our primary qualifying criteria. These criteria are centred around quality and transparency. The primary criterion is that the project has applied an additionality test, or has otherwise provided sufficient information on how it is deemed additional. The other criteria centre on third-party auditing and public disclosure of sufficient information to assess the project’s claims. All three act as limiting factors for whether BeZero accepts a project to be rated at all. Additionality - i.e. whether, in the absence of carbon revenues, the avoidance or removal activity would be viable - is the founding principle of a carbon credit project. Consistent with this, additionality is a limiting factor for the rating from the outset of the analytical process. For all projects, sufficient public disclosure of project claims includes crediting calculations, registry issuance (inclusive of buffer pool allocations), project boundaries and applied methodologies (and their versioning). Our bottom-up assessment considers all publicly-available project documentation and data, including that provided by the standards body, registry, or project developer, and any information from third-party sources, and data sourced using our internal models.
See the following resources for more information on how we rate ARR projects:
Webinar recording - From satellites to ratings: impartial views on carbon credit quality