デジタル化水準評価に基づく貴州省農業炭素排出の影響要因分解

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🔬研究者:農業分野の炭素排出要因分解とデジタル化の動的影響を定量化した手法（LMDI+VAR）は、他地域・他セクターへの応用研究に有用。

🏢実務担当者:農業関連企業や食品企業は、デジタル化投資が排出削減に直結する条件（精密投入管理、家畜ふん尿処理、クリーンエネルギー代替）を理解し、Scope3削減策に活用できる。

🏛政策担当者:農業デジタル化政策と炭素削減政策の相乗効果を設計する際、デジタル化が生産拡大を促すリバウンド効果を考慮すべきという示唆を提供。

The digital empowerment of agricultural carbon emission reduction plays a crucial role in surmounting emission - reduction bottlenecks and attaining the Dual Carbon goals. This research measured the agricultural carbon emission and the digitalization level in Guizhou Province from 2013 to 2022. An LMDI decomposition model integrating the digitalization level was established to analyze the influencing factors, and a VAR model was employed to forecast the evolving relationships. The results are as follows: (1) Throughout the study period, the agricultural digitalization level demonstrated a gradual upward tendency, while the carbon emission generally presented an “N - shaped” pattern. (2) The influence of digitalization on carbon emission dynamically evolved from “significantly promoting an increase” to “weakly promoting an increase”. The emission - reduction factors (the energy intensity effect and the digitalization - induced energy consumption effect) jointly led to a reduction of 31.68 million tons in emission, whereas the emission - increasing factors (the agricultural economic scale effect and the digitalization - induced production effect) resulted in an increase of 34.83 million tons in emission. (3) Forecasts suggest that the synergistic interaction among these four effects from 2023 to 2030 could achieve a net reduction of 9.25 million tons, facilitating the transformation of emission from an “N - shaped” to an “M - shaped” pattern. The impulse response analysis reveals that for most effects, there are positive driving forces in the first two lags, and all effects transition to inhibitory roles and converge after the third lag. These findings indicate that digitalization alone does not necessarily lead to agricultural carbon emission reduction; its environmental benefits depend on whether digital inputs improve energy efficiency and resource allocation rather than stimulate production expansion. Therefore, Guizhou should prioritize digital applications in precision input management, livestock manure treatment, and clean-energy substitution to promote the coordinated development of agricultural digitalization and carbon reduction.

• openalex https://doi.org/10.3389/fenvs.2026.1901851first seen 2026-09-18 04:48:54