The promise of carbon credits is unlocking millions of dollars of private money to fund climate change solutions that are hard to finance through typical revenue models. But the criticisms around these carbon credit projects might make corporations wary of investing in them — worried they will be the subject of a ProPublica article or John Oliver segment.
The age-old mantra with carbon credits is that some are good, some are bad and it’s hard to know which is which. Activists, investigative journalists and comedians will highlight and shame the bad projects. Corporations, project developers and registries will tout the good ones. But neither approach actually resolves the core issue — that we need to encourage the right kinds of projects that are actually reducing emissions and stop funding the ones that aren’t.
But there are wonky scientists at carbon credit organizations working to improve carbon credits bit by bit, inch by inch, tiny nuance to tiny nuance. Here are four things that are helping carbon crediting get more accurate, precise and credible.
1. Dynamic baselines
Baselines, the carbon that would have been sequestered or emitted without the intervention, are one of the carbon crediting mechanisms that often come under fire in investigative articles calling out bad projects. Quotes from landowners such as "these trees were never going to be cut down" are devastating to credibility and impact for both the project and the buyer. These questions about additionality steam from simplistic baselines.
According to Guy Pinjuv, director of forest science and policy at Pachama, a startup working to improve carbon credits with artificial intelligence (AI) and machine learning, traditional baselines for avoiding deforestation look at the project region’s historical deforestation rate and projects that into the future. So baselines are primarily a static percentage that isn’t updated until a revelation every decade or so. But as every statistician will tell you, past performance is no indication of future performance.
Dynamic baselines are a new way forward. Using satellite monitoring, including light detection and ranging and cloud-penetrating radar, combined with machine learning and AI, organizations such as Pachama and Verra, a carbon credits regulatory agency, can create more accurate baselines that are based on what is actually happening in the region instead of what happened in the past.
Dynamic baselines pick "control" areas that are as similar as possible to the carbon credit project based on factors such as distance to roads, distance to waterways, slope, elevation, vegetation density, trunk shape, public or private ownership and type of forest. Each factor has a significant impact on the amount of deforestation an area is at risk for. Then the carbon crediting project is compared to these "control" regions over the project's lifetime.
"You don't have to predict the future," Pinjuv said. "You can just watch it."
While this may seem like a very straightforward scientific method — having a control group compared to an experimental region — according to Pinjuv, this type of methodology has been out of reach for deforestation projects because of the crushing amount of computational power needed to extrapolate thousands of cofactors to possible baselines. The machine learning and AI capabilities developed over the past few years not only allow this type of calculator to be possible, but also help identify regions that are more similar to the project than any human eye ever could.
2. A global satellite monitoring program
Because the carbon economy is largely voluntary at the moment, the carbon crediting projects are disjointed and separate entities don’t have consistent communication with one another. And according to Pedro Barata, co-chair of the Integrity Council for Voluntary Carbon Markets’ expert panel, it’s a project-by-project monitoring scheme.
A monitoring system like this could answer questions like: What happened to the project scenario? What happened outside of the project? Are there trends in the species type of the population?
"We often are not seeing the total outcome," he said. "[We need] a global monitoring system that would allow for finding out exactly what is happening in any particular plot of land that is part of a carbon crediting project."
Right now, projects rely on third-party verifications and protocols, ground truthing and piecemeal satellite monitoring. All of these things will probably still be necessary even if a global monitoring system is launched, but a program like this would drastically reduce costs for verification organizations and project developers and allow for better monitoring of projects that are usually in remote and hard-to-access locations.
A monitoring system like this could answer questions like: What happened to the project scenario? What happened outside of the project? Are there trends in the species type of the population? Have there been fluctuations in the amount of carbon sequestered or types of trees?
This type of data is really important to get a more robust calculation of exactly what the projects are crediting and if it is just business as usual. And consequently, this type of monitoring would also help dynamic baselines.
"Academic groups tell us that actually, [a global monitoring program] is eminently feasible. This is not something that is pie in the sky," Barata said. "With local funding, we could have this rolled out across the globe in a way that would provide certainty and robustness in terms of the monitoring that we're currently lacking."
Barata made sure to emphasize that our lack of a global system is not necessarily because of a lack of goodwill, or due diligence on anyone's part, but because they are huge areas that are difficult to monitor and difficult to understand. The Tel Aviv-based company Albo is working on analyzing satellite imagery to create this global program.
3. Digitize everything
Like many institutions, carbon crediting is still working on entering the 21st century. Data management and digitization are extremely hard but necessary in order for crediting to be the most efficient, accurate and accessible version of itself. Verra is leading the charge with the goal of complete digitization of all processes.
According to Steven Zwick, senior manager of media relations at Verra, this would include digitizing existing methodologies, developing a digital project template that will enable greater accuracy and efficiency in project development, as well as validation and verification digitization.
From the moment a project idea note shows up to the moment a credit is issued, the entire timeline should have a digital footprint. This will speed up the process of developing a project, make project documentation more accessible to researchers, reporters and companies and make the paperwork more uniform, which increases functional transparency.
4. Climate warehouses
Accounting, and more specifically double counting, is another area of high concern for carbon markets. Case in point, the most contentious debate at last year’s COP was Article 6, the rules for how companies will trade credits without double counting.
"A lot of the problems that we're having now with environmental integrity in relation to accounting and avoidance of double counting, come from the fact that the carbon parenting programs work as separate islands," Barata said.
The World Bank is working on addressing this with the Climate Warehouse project, a plan to gather together all carbon crediting programs and connect all the registries to create a single registry infrastructure that would avoid the risk of one credit issued under multiple entities.
While Barata thinks it would be hard to find a double-counting misuse like this among the big established registries right now, as the market is very small, this is less of a concern. But as the carbon credit market grows, which it is predicted to do at an exponential rate, the likelihood of double-counting problems will also increase.