How Data Elements Drive Net Carbon Emission Efficiency in Agriculture

Abstract

Under the framework of global climate governance and China's "Dual Carbon" strategy, this study systematically investigates the driving mechanisms and practical pathways for data elements to enhance agricultural net carbon emission efficiency. The research demonstrates that a synergistic digital management system integrating monitoring, optimization, and trading functions can significantly improve carbon efficiency in agricultural production through precision management enabled by digital technologies such as IoT, big data, and blockchain.The findings indicate that data elements primarily drive agricultural low-carbon transformation through reconstructing production patterns, optimizing resource allocation, and establishing intelligent decision systems. This study innovatively proposes a data-driven agricultural carbon governance framework that offers an "inclusive service" solution to bridge smallholder producers with carbon markets, contributing substantial theoretical guidance for achieving green and low-carbon agricultural development. Furthermore, the research systematically examines existing technological adaptation challenges and institutional barriers in market mechanism formation, providing valuable insights to guide future studies and policy formulation.