Carbon accounting and modeling for climate solutions: Demonstration of enabling technologies скачать в хорошем качестве

Carbon accounting and modeling for climate solutions: Demonstration of enabling technologies

Brandon University Faculty of Science Seminar Series 2025-26 https://www.brandonu.ca/science/seminar-se... November 28, 2025 Naeem Abbasi Agriculture & Agri-Food Canada Carbon accounting and modeling for climate solutions: Demonstration of enabling technologies Abstract: Healthy soils have cascading effects on planetary health. They can sequester one-third of anthropogenic greenhouse gas emissions through adoption of beneficial management practices. This presentation synthesizes field research, biogeochemical modeling advances, and digital platform development to demonstrate pathways toward actionable climate solutions. Field measurements of N₂O and CO₂ emissions in corn-soybean rotations inform evidence-based management practices for emission reduction. Machine learning and biophysical models (DNDCv.CAN and EPIC) enable prediction of emission outcomes across diverse management scenarios. Performance metrics demonstrate robust accuracy in carbon dynamics simulation. Two enabling technologies address the accessibility challenge in complex modeling. The EPIC User Interface features intuitive design with built-in validation. The DNDC Model Calibrator utilizes Bayesian optimization for automated parameter calibration. These tools expand model accessibility to broader scientific communities. Soil-based solutions alone are insufficient for climate mitigation. Comprehensive carbon accounting across all sectors becomes essential for fossil fuel reduction and clean energy transition. The Teal Climate platform demonstrates streamlined GHG tracking capabilities across diverse sectors. Finally a provocative hypothesis is proposed where carbon accounting functions as an observer effect analogous to quantum physics principles. Measurement itself may shift collective behavior from emission-blind to emission-conscious defaults. This could potentially accelerate reduction outcomes independent of regulatory frameworks. Biography: Dr. Naeem Ahmed Abbasi is a Research Scientist at Agriculture and Agri-Food Canada. He specializes in agricultural greenhouse gas modeling using biophysical models and machine learning. Dr. Abbasi has developed enabling technologies including the EPIC User Interface, DNDC Model Calibrator, and Teal Climate carbon accounting platform. He completed his PhD at McGill University. His work bridges field research with digital innovation to advance climate solutions in agriculture and corporate sectors.