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Building a system to evaluate the quality of carbon crediting using generated AI.
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October 4, 2024
Osaka Gas Co., Ltd.
Osaka Gas Co., Ltd. (President: Masataka Fujiwara) has built a system to evaluate the quality of carbon credits using AI in the world's first initiative.
Carbon credits are certified to allow the trading of the quantity of reduction or removal (absorption) of greenhouse gases such as carbon dioxide (hereinafter referred to as "CO2") among nations and companies. Carbon credits are mainly classified into emission reduction types generated by upgrading existing facilities to more efficient ones, and absorption types created by fixing CO2 in plants or soil and removing CO2 from the atmosphere, such as afforestation and biochar application to farmland.
In recent years, various companies have been increasing efforts to offset unavoidable GHG emissions with carbon credits after making efforts to reduce GHG emissions to achieve carbon neutrality. Therefore, it is estimated that up to 100 trillion yen of credits may be needed globally by 2030, and it is expected that the development of credits will continue to accelerate in the future.
Properly evaluating the quality of carbon credits is crucial to avoid greenwashing and price volatility risks, and can be advantageous in business.
We have developed a system using AI to evaluate the quality of carbon credits. We plan to expand the areas where the system can be applied in the future.
In this system, we evaluate the quality by analyzing carbon credit creation project plans with AI, assessing the consistency between the criteria set during actual credit certification and those set by initiatives and rating agencies. We have confirmed that it achieves high accuracy within the range compared with past evaluations by rating agencies. By utilizing AI, it is possible to comprehensively evaluate a vast number of carbon credit creation projects, which may enable the relative evaluation of the quality among these projects in the future.
As a result, compared to the typical period of one to two months required for initial evaluations by third parties, it is possible to drastically improve this process to just a few dozen seconds.
In the future, we plan to continue developing the system further, such as improving the evaluation accuracy, and also anticipate collaborating with related conglomerates for further improvement of this system and expanding into new application areas. Through such initiatives, we aim to deliver high-quality carbon credits to our customers. Additionally, we aim to collaborate with partners by providing licenses for this system, forming a crediting trading platform for utilization, and exploring all possibilities together to contribute to avoiding and minimizing greenwashing across society.
The Green Innovation Fund project is a fund project of about 2.8 trillion yen created to aim for achieving carbon neutrality by 2050, to accelerate innovation through structural changes in the energy and industrial sectors, and through bold investments.
*1: | Based on our research. |
*2: | Carbon Credit World Market Report 2024 (Global Information Co., Ltd.). |
1. Evaluation system for carbon credit quality using generated AI developed by us. | |
- | AI developed to analyze the project plan of the carbon crediting creation project (PJ). |
- | Evaluating the quality of carbon credits by assessing alignment with over 100 criteria (1). |
- | Since AI can comprehensively evaluate vast projects, there is a possibility of achieving relative quality evaluation among projects in the future (2). |
2. Image of using this system | |
- | The creation of carbon credits progresses in the flow of certification based on the certification period of the credit creation project (PJ) plan → development of the project (credit creation) → issuance of credits and credit rating by a credit rating agency → trading. |
- | By evaluating more projects in advance with this system from the pre-development stage of credit development, high-quality projects can be selected and investment or credit purchases can be decided quickly. |
- | By evaluating the quality of credits using this system at the pre-transaction stage, quality risks such as greenwashing can be easily confirmed. |
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