Carbon Sequestration Project

Reducing the uncertainty around the carbon mitigation potential of forests.

Since the industrial revolution, there has been a noticeable increase in anthropogenic emissions, especially carbon dioxide. In recent times there have been multiple initiatives and agreements throughout the world to work towards a reduction in emissions as well as to develop better carbon mitigation strategies.

Emissions and removal need to be at a careful balance to avoid worldwide climate change and disastrous effects, and a large influencer of this balance is forests and general tree cover.

Increases in reforestation efforts have the potential to remove large quantities of carbon from the atmosphere. In addition to reforestation initiatives, there are current tools and models that aim to assist people in understanding the viability and benefits of reforestation in given areas.

The Paris Agreement contained proposals for different metrics of emission reduction. To aid in keeping track of the proposals, the CAIT Climate Data Explorer is a WRI tool designed to track the nationally determined contributions proposed by each country.

Griscom et. Al. (2017) performed a study that argued that reforestation is the single largest “natural climate solution” for mitigating climate change, and many nations have prioritized reforestation in their NDCs. Along with this, the Organization for Economic Cooperation and Development has a compendium of the mitigation policies of its member countries in terms of energy, agriculture, forestry, industry, and waste.

Scope

We aim to reduce the uncertainty around the carbon mitigation potential of forests by narrowing the range of estimates of the size of land available for reforestation and by more accurately determining carbon sequestration rates worldwide.

Goals

As our product will ideally create an interactive visualization of the information we have gathered, decision-makers should be able to see the actual carbon mitigation potential of the lands they manage, providing more encouragement to implement such reforestation programs in these areas.

The visualization will provide an accessible way to communicate the scale of impact of existing and proposed reforestation programs to those impacted by their implementation. Additionally, the availability of the data and model to those in fields such as climate modeling and greenhouse gas accounting will allow others to use this work to build climate change scenarios based on partial or total implementation of reforestation programs.

Making everything open-source, publicly available, and with detailed documentation about the process and the uncertainty in the predictions will make this project invaluable to decision-makers and those who will build upon this work.

Research Team

Data Catalog

Carbon Sequestration is part of an AI for Good project series, between the AI for Good Foundation and the Applied Data Science with Venture Applications Course at SCET, UC Berkeley.

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