AI can be used successfully use to track carbon emissions, carbon footprint, air quality monitoring and forecasting, waste management and carbon credits trading

1. The use of AI in carbon credit management
Sergio Cruzes, MsC, MBA, PMP – May 2023
Network Engineer at Ciena (scruzes@ciena.com)
sergio_cruzes2002@yahoo.com
1. Abstract – AI can be used successfully use to track carbon emissions, carbon footprint, air quality
monitoring and forecasting, waste management and carbon credits trading
2. Introduction
The terms carbon offset and carbon offset credit (or simply “offset credit”) are used interchangeably,
though they can mean slightly different things. A carbon offset broadly refers to a reduction in GHG
emissions – or an increase in carbon storage (e.g., through land restoration or the planting of trees) –
that is used to compensate for emissions that occur elsewhere. A carbon offset credit is a transferrable
instrument certified by governments or independent certification bodies to represent an emission
reduction of one metric tonne of CO2, or an equivalent amount of other GHGs (see Text Box, below). The
purchaser of an offset credit can “retire” it to claim the underlying reduction towards their own GHG
reduction goals [1]
A carbon footprint is the total amount of greenhouse gases (including carbon dioxide and methane) that
are generated by our actions [2].
A carbon credit represents 1 tonne of CO2e that an organization is permitted to emit. Carbon credits
only exist in markets with cap and trade regulations. Management teams that emit less than their limit
may resell carbon credits on the corresponding carbon market [3].
3. AI in carbon and footprint emissions management
Carbon credits can be managed by companies by the use of AI to track carbon emissions. This can be
done by [4]:
- The use of IoT devices
- Tracing manufacturing supply networks through calculations of embodied carbon emissions (e.g
building footprint construction and waste removal and recycling)
- Monitoring of carbon emissions through object recognition
- Air quality monitoring and forecasting: better accuracy predictions as pollutants have nonlinear
behavior
- Smart management of waste: through waste site sorting and prevention of illegal disposal
through the use of IoT sensors and cameras.
- Carbon credits trading
- Equipment monitoring: machinery usage including fuel consumption
- Carbon credits monitoring: tracking company’s carbon credit in an automated manner
(monitoring emissions, tracing carbon footprints, auditing and trading carbon credits, all this
based on AI, IoT and Blockchain)
- Carbon emissions forecasting: estimating future emissions via carbon footprint

2. 4. Conclusions
This article tries to explain in brief way what carbon credits are and how AI helps in carbon
emission monitoring and carbon credit management.
5. References
[1] https://www.offsetguide.org/understanding-carbon-offsets/what-is-a-carbon-
offset/#:~:text=A%20carbon%20offset%20broadly%20refers,for%20emissions%20that%20occur%20else
where.
[2] https://www.nature.org/en-us/get-involved/how-to-help/carbon-footprint-calculator/
[3] https://corporatefinanceinstitute.com/resources/esg/carbon-credit/
[4] “The concept of “Carbon Credit” in the construction industry: A case study of viAct’s scenario based
AI in carbon credit management”, Gary Ng, Hugo Cheuk, Surendra Singh, Barnali Sharma, Baby Sharma,
2022