Calculation and analysis of agricultural carbon emission efficiency considering water–energy–food pressure: Modeling and application

Abstract

Agricultural carbon emission efficiency (ACEE) measurement, a tool for effectively achieving sustainable development goals, has garnered much attention. However, the impacts of resource pressures such as water, energy and food on ACEE have been overlooked, and the high dimensionality of the measurement model and insufficient sample data can easily distort the measurement results. Therefore, from a green development perspective, we established a new ACEE measurement framework considering the water–energy–food pressure index and a new integrated ACEE measurement model (CSMA-PPE-USSBM) that includes chaotic maps, the slime mould algorithm (SMA), projection pursuit evaluation (PPE) and the undesirable super slack-based measure (USSBM). The model was used to calculate ACEE in 13 prefecture-level municipalities in Heilongjiang Province, China, and analyze its spatiotemporal evolution and possible causes. The results showed that this model avoids the above problems. The reliability coefficient and stability coefficient reached 0.962 and 0.971, respectively; ACEE in Heilongjiang Province has much room for improvement, but there are obvious differences in carbon emission efficiency in different carbon emission type regions. The key driving forces of ACEE variation can generate significant scale effects. Provincial driving factors can affect ACEE variation in prefecture municipalities, where the influence range is limited or the influence of driving factors gradually emerges. The research results provide a theoretical reference for accurately measuring the regional ACEE and analyzing the driving mechanism of ACEE and green agricultural development.