Using AI to Revolutionize Carbon Offset Measurement

The idea of carbon offsetting first came in the late 1980s when leaders worldwide realised that they needed to take action to stop climate change. The first carbon offset project was an agriforest in Guatemala.

Then in 1992, the Kyoto Protocol outlined the first offset provided under the Clean Development Mechanism, allowing developed countries to compensate for their emission by investing in environment-positive projects in developing countries. However, the voluntary carbon offset credits started after 2005. Other entities like businesses and regulated companies aside from just governments also wanted to offset their emissions, and the carbon offset markets have expanded (Normand, 2022).

Since then, the concept has grown and been embraced by countries, businesses, and corporations as a solution to balance their carbon emissions or as a tool to achieve net zero.

Carbon offsets are a way to compensate for emissions by funding an equivalent carbon dioxide saving elsewhere. (Carbon Offsetting, n.d.). Carbon offsetting is used to balance these emissions by helping to pay for emission savings in other parts of the world.

Our everyday actions at home and work consume energy and produce carbon emissions, such as driving, flying, and heating buildings.

Essentially you are paying an offset provider or a company to reduce your emissions by planting a forest, for example, to absorb it or capture and store it from the atmosphere.

As with everything else, carbon offsets have their limitations.

The main thing is that it only reduces carbon emissions that have already been emitted and not stopping activities that are the source of emission, which is at the core of the problem. Second, not all offset projects are the same in efficiency, and offsets must be additional. Additionally, the reductions in emissions achieved by the project must be “above business as usual.” That means they would only have happened if the project had been implemented. Finally, offsets can only remove a small fraction of all our carbon emissions (Smoot, n.d.)

Then there is also a problem of measuring offsets accurately and transparently to ensure that it achieves climate reduction targets.

NZ Herald reports that A 24-year-old New Zealander, Saurav J. Bansal, founded the company GAIT (Green Artificial Intelligence Technology), targeting New Zealand’s carbon market to help them remove the guesswork in their jobs.

According to Bansal that at the moment, there is no way to tell whether the carbon credit that many organisations are counting is accurate, and “there are a lot of fraud or transparency issues, a lot of greenwashing, a lot of double counting of carbon credits” (The Kiwi leading, 2023).

The article says that the GAIT’s machine-learning software technology platform measures carbon abatement digitally, in real-time, combining flux sensors, spatial data, and artificial intelligence to create a robust and highly accurate form of measurement.

“GAIT’s technology sees sensors collect data on atmospheric gases and satellites collect spatial data while the platform (made up of internet-of-things, cloud infrastructure, and artificial intelligence) analyses it. That gives carbon projects – including tree-planting, conservation work, waste conversion, and renewable energy – better and more immediate awareness of their environmental impact.”

Bansal says that his company currently works with the Lake Hawea Station, one of the country’s premier high-country farms, supporting their vision to become ten times carbon positive.

He adds that the technology can support businesses that want to make a change, but first, knowing how to measure that change and what that change is essential.

The GAIT website says the company uses flux sensors based on a highly established scientific principle. Our flux sensors are based on a highly established scientific principle: Eddy Covariance. Eddy Covariance is an atmospheric measurement technique used to measure and calculate atmospheric metrics.

Carbon flux

A carbon flux is the amount of carbon exchanged between Earth’s carbon pools – the oceans, atmosphere, land, and living things – and is typically measured in units of gigatonnes of carbon per year (GtC/yr) (Carbon flux, n.d.).

The Earth’s carbon is exchanged globally in what is known as the carbon cycle or the movement of carbon between land, oceans, the atmosphere, and living things. This cycle swaps immense quantities of carbon each year (Carbon flux, n.d.).

Carbon flux (n.d.) explains that the carbon cycle balances almost perfectly naturally. However, when humans introduce carbon buried underground, this presents an imbalance due to emissions from increased burning of fossil fuel, cement production, and land-use change. The net increase in emissions from human activities is responsible for climate change problems like rising global average temperatures and ocean acidification (Carbon flux, n.d.).

Some studies on carbon flux measurement

According to a study, the EC technique was first proposed in the early 1950s to measure the vertical flux of CO2, water vapour and energy between ecosystems and the atmosphere (Skinner and Wagner-Riddle, 2012).

The study “Analysis of the 21-years long carbon dioxide flux dataset from a Central European tall tower site” notes that it was not until the 1990s that the technology was established and revolutionised carbon cycle research.

Using the technology, the associated scientists started to provide rich and extremely valuable datasets on the carbon balance components of terrestrial ecosystems. The study says that as of January, there are 1421 known active sites with a total of 2049 known measurement locations and 608 inactive sites.