Projected Net Carbon Emission Limit (PNCEL): A Dynamic Model for Carbon Management in Agroforestry Systems

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:Provides a dynamic modeling approach for net carbon balance in agroforestry, with potential for AI integration.

🏢実務担当者:Offers a tool for measuring and projecting carbon footprint, supporting sustainability reporting and certification.

🏛政策担当者:Informs design of performance-based incentive programs and agroenvironmental policies.

Purpose | Agricultural and agroforestry systems have been shown to have a significant impact on greenhouse gas (GHG) emissions, whilst simultaneously presenting considerable opportunities for carbon sequestration. Nevertheless, the quantification and projection of their net carbon balance continue to represent a considerable challenge. This study introduces the Projected Net Carbon Emission Limit (PNCEL), a new metric applied in a dynamic model designed to measure and project the carbon footprint in agroforestry systems by integrating direct emissions, soil carbon sequestration, and net carbon balance. The model aims to support sustainable business management, inform public policy formulation, and facilitate academic research on soil management's impact on emission reductions. Methodology/Approach | The PNCEL model integrates advanced temporal monitoring with carbon management metrics for agricultural and agroforestry production chains, enabling the assessment of the net effectiveness of mitigation strategies and providing evidence-based operational recommendations. The model incorporates data from GHG inventories, aligning with international standards such as the GHG Protocol and ISO 14064. The model employs dynamic equations to calculate Absolute GHG Emissions, Net Carbon Balance (NCB), and the Projected Net Carbon Emission Limit (PNCEL), allowing the net effectiveness of mitigation strategies to be assessed and providing operational recommendations for long-term scenarios. Although initially applied in viticulture, the model's flexibility allows for its adaptation to other sectors, including olive cultivation, fruit production, and integrated agroforestry systems. Beyond its application in sustainable business management, the model can be utilised by regulatory bodies for public policy formulation and by academic institutions to study the impact of soil management on emission reductions. Expected Results | Future projections indicate that the PNCEL can be enhanced through integration with machine learning and artificial intelligence, expanding its applicability to a broader range of agricultural activities and evolving into a standardised carbon neutrality index. The model's dynamic and flexible approach supports the creation of tailored decarbonisation strategies, contributing to the sustainable transition of agroforestry systems and the achievement of global climate goals, such as those outlined in the Paris Agreement. Practical Implications | The model holds significant potential for guiding agroenvironmental policies, enabling the design of performance-based incentive programs, supporting carbon certification schemes, and informing extension services for farmers seeking climate-positive management. However, its full institutional adoption will require further empirical validation and robust verification mechanisms for farmer-reported data.

• openalex https://doi.org/10.5281/zenodo.21672940first seen 2026-07-31 06:01:54