Decarbonization Framework to Accelerate The Carbon Net-zero Pathway for Enterprises

Abstract

Enterprises are under significant pressure from investors, consumers, and policymakers to act on climate change mitigation by disclosing their GHG emissions and committing to reduction of emissions from their industrial activities. More than 20% of the world's largest companies have set long-term net-zero targets but need technology to measure and reduce their emissions. In this talk, we present a comprehensive framework that includes an augmentation of spatio-temporal contextual data, carbon emissions accounting engine, and anomaly detection to identify the performance of individual assets or operations. The framework leverages explainable AI to derive useful insight about various influencing parameters and performs counterfactual analysis to recommend the set of optimal values for the intervenable parameters to reduce the overall carbon footprints.