Learn about Blake and his research on how trees factor into Carbon Credits

Hi, Green Llama lovers. I’m Blake Montgomery, and I am a student majoring in Biology at ETSU. This summer I have had the opportunity to work alongside Green Llama’s marketing department while also researching carbon offsets with ETSU’s entrepreneurship department. As someone who loves the outdoors, I was beyond pleased to spend my summer working with such eco-friendly people.

My undergraduate research project focused on carbon credits and how these are calculated, verified, and sold. A carbon credit or carbon offset is a tradable permit that allows the owner to release a certain amount of carbon into the atmosphere. One carbon credit is equivalent to one metric ton of carbon dioxide (CO₂). With more and more businesses and people wanting to reduce their carbon footprint, carbon credits are increasing in value and popularity. The difficulty of calculating carbon credits is being able to do it quickly and accurately. While there are several types of carbon offsets, our research focused on nature-based sequestration, and more specifically trees. Trees sequester carbon through the uptake of CO₂ from the air. The CO₂ is converted into biomass, which is essentially the major components of the tree’s trunk and leaves. It’s estimated that trees in the European Union contain up to 9.8 billion tons of carbon (https://unece.org/forests/carbon-sinks-and-sequestration). The amount of carbon sequestered by a tree varies across tree species and even within the same species year to year. Factors affecting this include climate, rainfall among other factors.

 One difficulty with crediting carbon by natural sequestration is that sellers can oversell sequestered credits with potentially multiple buyers for the same piece of land. To ensure validity, carbon credits should be verified in order to confirm its value. Our goal is to send out drones to capture images of large plots of land and use those images to identify the tree species, height, diameter, canopy, number of trees, and percentage tree coverage within a given are of land. This data will allow us to calculate how much CO₂ the land absorbs each year efficiently and accurately. These images would also be used to show the buyer what land their carbon credit came from and ensure that the piece of land has not been sold to other buyers. Creating accurate and reliable carbon credits will allow for more sales of these offsets and lead to a more sustainable way of living. How can you reduce your carbon footprint?