Artificial Intelligence GHG Monitoring for a Voluntary Carbon Certification

Generating carbon credits in rural and wetland lagoon environments is important for the economic and social survival of the same. There are many methodologies to study and certificate the Carbon Sink such as the ISO 14064, VCS VERRA, UNI-BNEUTRAL, GOLD STANDARD and others. Many methods done before 2018 are obsolete since research has developed greatly in recent years. The methods are all different, but they share a continuous and real monitoring of the environment to ensure a true CCS (Carbon Capture and Storage) action. In the case of absence of monitoring, the method uses a system of provision of carbon credits called “buffer”. This system allows maintaining a credit-generating activity even in the presence of important anomalies due to adverse weather events. This research shows the complex analytic web of the different sensors in a continuous environmental monitoring system via GSM (Global System for Mobile) Communication and IoT (Internet of Things). By 2011, a monitoring network was installed in the wetland environments of Northern Italy Venetian Lagoon (UNESCO heritage) and used to understand and validate, the CCS action. Thingspeak cloud platform is used to collect data and is used to send alert to the user if the biological sink is reversed to emission. The obtained large dataset was used to prepare a AI (Artificial Intelligence) model “CCS wetland forecast” by Google COLAB. This model can fit the trend to avoid the direct and spot chemical field analysis and demonstrate the real efficacy of the model chosen. This network is now implemented by the Italian national method UNI PdR 99:2021 BNeutral generation of carbon credits.