How AI helps sustainability, helps individuals earn carbon credit

WEDNESDAY, JANUARY 10, 2024
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How AI helps sustainability, helps individuals earn carbon credit

Artificial Intelligence (AI) has the potential to play a significant role in promoting world sustainability and help individuals earn carbon credit by assisting in various aspects of carbon accreditation.

What is carbon credit?

Carbon credit is a tradable certificate representing the measurable and verifiable emission reductions from certified climate action projects. The concept is used as a tool to reduce greenhouse gas emissions, a major contributor to climate change. Here's a brief overview:


Can individuals earn carbon credit?

Yes, individuals can earn carbon credit, though the process can be more challenging and less common than for larger entities like corporations or governments. There are applications that help users earn carbon credit via certified activities.

What activities can earn carbon credits?

Based on the article's description of carbon reduction projects, here are suggestions for projects that individuals can undertake to earn carbon credit:

1. Forestry and land use: Individuals can engage in small-scale reforestation or afforestation projects, planting trees in their local community or on private land. They can also participate in sustainable land management practices, such as maintaining or creating green spaces that absorb CO2.

2. Renewable energy: Installing solar panels or small wind turbines on individual properties can contribute to renewable energy generation. Individuals might also participate in community renewable energy projects or advocate for the use of renewable energy sources in their local area.

3. Household and community devices: Implementing energy-efficient devices in homes and encouraging their use in the community can be a way to contribute. This might include energy-efficient lighting, heating systems, and other home appliances that reduce carbon emissions.

4. Blue carbon: Individuals living near wetlands, marshes, or coastal areas can participate in local conservation and restoration projects. This might involve volunteering for clean-up efforts, planting native vegetation, or supporting local conservation groups.

5. Waste management: Starting or participating in community recycling or composting programmes can help manage waste more sustainably. Individuals can also practise and promote waste reduction and recycling at home and in their communities.

6. Agricultural land management: For those with access to agricultural land, practising carbon farming techniques like no-till farming, planting cover crops, or using sustainable agriculture practices can help sequester carbon in the soil.

7. Transportation: Individuals can reduce transportation emissions by using electric or hybrid vehicles, promoting and using public transportation, biking, or walking. They might also engage in or support local initiatives aimed at improving sustainable transportation infrastructure.

All these projects not only capture or avoid greenhouse gas emissions but also often contribute positively to the local community and environment, aligning with the United Nations Sustainable Development Goals.


How can AI help facilitate these activities?

AI can play a significant role in facilitating and enhancing the effectiveness of carbon credit-related activities. Here's how AI can be applied to each of the project types mentioned:

For waste management, AI can aid in sorting recyclables and managing waste treatment facilities. For instance, individuals can deposit plastics or bottles at designated drop-off points. Here, AI-enabled vending machines, through computer vision AI and other sensors, can assist in categorising items, correctly crediting the participating individuals. At coffee shops, individuals can bring their own cups, and the receipt will indicate this action. AI, using OCR technology, can scan the receipt and credit the action in an application. OCR can also help identify items purchased on the receipts, for example plant-based food, certified garments, each of which may earn different carbon credits.

In agriculture and land management, AI can analyse soil data to optimise farming practices for carbon sequestration. AI-driven drones can monitor fields for carbon sequestration effectiveness and also signs of deforestation.

As for renewable energy and usage, AI can optimise energy usage in buildings and help one act in a way that will conserve energy at home or office. Use of electric vehicles (EV) can be detected, verified at charging stations with intelligent AI suggesting how much credits one can earn optimally.

Across all these domains, AI can process vast amounts of data to provide insights, predict trends, optimise processes, and ultimately enhance the effectiveness of carbon reduction and sequestration efforts. Additionally, AI can assist in the monitoring and verification process required for carbon credit certification, making it easier and more efficient to validate the impact of these projects. While most behind-the-scene actions from AI will be implemented from the corporate side, we will be in touch with these systems at some points that assist the whole ecosystem to reduce carbon emission and waste. As environmental, social and governance regulations become obligation and economic incentives for businesses, there is no doubt individual consumers will also become a part of the equation and the ecosystem to earn something from being a good world citizen. It is also not too far-fetched to imagine an AI personal assistant who can suggest how we can alter our behaviour during the day to help the effort through real-time analytics of our activity and surroundings.

In summary, AI has the potential to play a significant role in advancing sustainability efforts and helping individuals earn carbon credits by optimising various processes and promoting environmentally friendly practices.


Author: Nattida Sanguansin, Managing Director and Co-founder of BUZZEBEES Co., Ltd.
Co-author: Pamornpol Jinachitra, CEO and Board of Director Member of AI GEN, Co., Ltd.

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