Reshaping Agriculture Eco-efficiency in China: From Greenhouse Gas Perspective

Incorporating emissions of greenhouse gases other than carbon dioxide into the metrics for agricultural eco-efficiency is critical for addressing climate change, given the significant role of agriculture in global emissions. Existing studies more focus on single carbon emission indicators and overlooks emissions of other significant greenhouse gases in measuring agricultural eco-efficiency, such as methane and nitrous oxide, leading to a potential underestimation of the true ecological impact of agricultural practices. Utilizing a dataset spanning 2000 to 2021 from China, this study for the first time includes methane and nitrous oxide in the assessment of agricultural eco-efficiency with SBM-DEA model, which defines a more standardized and accurate indicator system of agricultural eco-efficiency, and provides a more comprehensive framework for assessing the impact of agriculture on the environment. Furthermore, it rigorously assesses the variations in China’s agricultural eco-efficiency before and after accounting for multiple greenhouse gases. The study found that, first, before and after embedding a wide range of GHGs, China’s agricultural eco-efficiency overalltrends are basically the same, both showing slow growth in fluctuation, but the ecological impacts of non-CO₂ emissions are underestimated. Second, the agricultural eco-efficiency among China’s provinces is characterized by “high in the northwest and low in the southeast”, with spatial heterogeneity in the efficiency level. Last, the underestimation level of the balance of production and marketing area is the highest.This study proposes a novel approach by recommending the integration of various greenhouse gas emissions into the evaluation of agricultural eco-efficiency. It explores cooperative strategies for reducing emissions across several metrics. Such an approach offers quantitative insights that inform the development of green agricultural policies tailored to various regions.