A Roadmap for Scalable Carbon Trading — Part 2

7 min readJun 30, 2021


Photo by Ana Martinuzzi on Unsplash

Adding quality: monitoring strategies for more credible offsets

As the voluntary carbon markets prepare for much-needed scaling, maintaining high quality and integrity of credits is just as important as the quantity. In the first part of this series, we focused on the quantity. The article explains how monitoring developments are required to meet the needs projected for the future - up to fifteenfold increase needed by 2030.

In this part, we look at how monitoring tools can be used to develop quality carbon credits in scale, while also considering important ecological factors. For stronger and more resilient forests, we need to optimize for both carbon and biology.

What makes a good-quality carbon project?

A high-quality carbon project is a well maintained and supervised project. It provides real removals compared to the usual forest management scenario. The project does not increase emissions in neighboring areas or have other negative effects. And the positive effects sustain for the promised duration.

In other words, the project is additional, verifiable, non-leaking and durable.

Components of a good-quality carbon project. See Glossary for explanations of each component.

However, in the world of voluntary offsetting, the different projects and different certifiers have vastly different ways to meet these conditions. For example, avoided deforestation projects struggle to prove the claimed forest depletion rates. Improved forest management can also be tricky: when the trees are young and growing, the yearly capture will increase even without a project. In both cases, the baseline values are inconclusive.

Moreover, verifying processes and durability shields create unnecessarily high added costs, as we discovered in the first part. The extra costs and time required to complete these stages hinder many forest projects.

These core problems damage the reputation of forest carbon and need to be resolved before carbon trading can go mainstream.

To start solving these problems, we propose two effective monitoring strategies:

  1. Up-to-date data collection: Use real-time imagery to modernize project verification and tracking. If forest inventories are routinely updated with the most recent data, the carbon project can be verified more frequently and smoothly. However, many companies and standards currently rely on one-off pictures that quickly get old. This creates uncertainty and added costs for both the project developer and the credit buyers.

    CollectiveCrunch has a solution to change that. Our Linda Forest tool combines record many data sources and is constantly updating them. Thanks to the magnitude of data collected and the smart analytics, Linda Forest has been shown to estimate wood volume up to three times more accurately than field visits.

    Another trailblazer, Pachama implements a combination of remote sensing and machine learning to estimate carbon capture throughout project duration. However, there is more to be done in the carbon markets at large. We want to see further engagement in developing these tools and automation by more companies and carbon standards. With more extensive adoption, we get the best and most accurate models. After all, truthful models are a win-win: both the forest owners and the project developers benefit.
  2. Smarter data utilization: Remote sensing and data learning can answer the leakage and additionality doubts in the future.
  • Leakage can be better traced by monitoring an area larger than just the project forest. This paints a picture of the true effects of the carbon project. We could see if the neighboring areas started to drain after the project or if the bigger area is struggling with illegal logging activities or large insect invasions.
  • Additionality and baseline values can be more closely monitored if project data is processed with pre-existing knowledge from other similar projects. Forest models become more extensive and accurate for the specific locations and ecosystems as more projects are created. Historical stand data can be added to more clearly estimate the carbon trajectory. For example, the specific growth pattern of a young forest can then be mapped out, creating more accurate carbon models.

What makes a great-quality carbon project?

As we realize, creating a good-quality carbon project is harder than it seems. In many cases, forestry projects do not meet this bar consistently. However, truly purposeful improvements should look beyond carbon in a forest. In fact, carbon projects have a unique opportunity to also protect the ecological systems while adding value. A great carbon project combines carbon optimization with other ecological variables such as biodiversity.

Biodiversity loss is alarming. Global ecological diversity has been deteriorating alongside other pressing climate threats. While the exact causes are complex, the comorbid trend is clear: as temperatures climb up, more species seem to disappear. The graph 1 shows how temperatures and biodiversity have been developing since the 1970's.

Graph 1: The Living Planet Index (biodiversity index) tells us the percentage species we have left compared to reference point in 1970. Increase in temperature plots the increase in degrees celsius compared to pre-industrial levels of 1850.

As seen in the Graph 1 and reported by the World Economic Forum, we have lost 60% of our wildlife in the past 50 years. Owing to this, many scientists warn about a mass extinction.

However, forest carbon has the potential to help. By increasing and preserving global tree cover, more species can find suitable habitat. In the nature, animals and plants are interdependent with biodiversity often fueling itself: diverse plantation leads to diverse animal base.

Another good news is that promoting biodiversity is of everyone’s interest.

A forest with a natural distribution of flora and fauna is a strong forest, better prepared to handle insects and extreme weather conditions.

A wider range of species allows the forest to buffer these shocks because different species are more sensitive to different triggers. This benefits forest owners, managers, insurers, carbon project developers as well as customers buying carbon offsets. In addition, a diverse plant base actually increases soil carbon capture, according to studies.

All of this sounds very promising but unfortunately, the good prospects are often overshadowed by a narrow carbon vision —biodiversity is left out of consideration for two reasons:

  1. The highest biodiversity of wood rarely equals the highest forest carbon capture. The equation, however, can look very different, depending on location and other conditions.
  2. Current methods to track biodiversity are lacking and do not give the answers needed for biodiversity considerations in forest carbon. Similar to traditional forest inventory methods, biodiversity is usually monitored manually, through samplings, passive sensors and community reports. Data availability, freshness and accuracy vary greatly across regions. The end result is that it is currently too complicated to optimize for both carbon and biodiversity.

As a result, many afforestation and reforestation projects plant only the most high-carbon species at the cost of biodiversity. In fact, the Intergovernmental Panel on Biodiversity and Ecosystem Services (IPBES), estimates that most carbon removal attempts pose a risk for biodiversity.

To gather better inventories of forestation patterns that support both carbon capture and biodiversity, monitoring and smart data analytics can help:

  • Firstly, satellite imagery can distinguish different forest species based on features, such as yearly color variation. In the Northern hemisphere, the fall is a telltale season as different tree species turn orange and yellow at different times. Using this type of knowledge, we can map out what a diverse forest looks like in the region in question. Traditional biodiversity observations add a layer of information, improving the models.
  • Secondly, the resulting natural species distribution can be used as a reference point for carbon project goals.
  • Thirdly, the model can learn and adapt, producing more and more efficient carbon-biodiversity maximizations for specific areas.

CollectiveCrunch has already started the journey towards quality forestry projects by introducing Linda Planet - a carbon quantification tool for forest inventories.

In addition, our world-class analytics and expertise will soon be expanded to provide better carbon insights, streamlined carbon project management and biodiversity tracking. Get in touch to learn how we can help you find more transparent and effective ways of carbon modeling.

In the meanwhile, you can also follow our progress by subscribing to our newsletter here.

Glossary of terms

  • Additionality — The carbon sequestration that is claimed in the project would not have happened in “business as usual” scenario. In the usual scenario, often, there are not sufficient funds or technical knowledge to execute forest preservation/plantation.
  • Non-Leakage — The carbon removals of the project are negated or reduced by increased deforestation in neighboring forests. In this case, the project does not lead to true net positive effects or leads to much smaller capture than claimed effect. Examples of leaking deforestation include harvesting, insects and illegal logging.
  • Durability — Also known as permanency. Forestry projects have project spans of between 10–100 years. This ensures that the sequestration is not immediately released the next day. Some argue that longer-lasting removals should be more valuable. However, from environmental point any protection is better than no protection and even shorter durations have ecological value.
  • Verifiability —The claimed removals need to be able to be measured or observed. We advocate for a more remote sensing based system for tracking forestry projects. Currently, most carbon projects are certified by a carbon standard, a process including verifications and auditings by a third-party auditor.
  • Baseline value — Carbon capture or release wihtout the removal project. The carbon credits claimed by the project need to be produced on top of the business as usual situation, resulting in additional credits.




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