Exploring the application and decision optimization of climate-smart agriculture within land-energy-food-waste nexus

Abstract

The escalating threat of climate change from greenhouse gas (GHG) emissions increasingly threatens the stability of agricultural systems, emphasizing the pressing necessity to transition towards sustainable, low-carbon practices. Climate-smart agriculture (CSA) is an evolving approach to balance heightened crop productivity, reduced GHG emissions, and enhanced resource adaptability to climate change. A comprehensive model was developed to facilitate the sustainable and coordinated development of land, energy, food, and waste nexus systems. This study seeks to tackle the pressing necessity by incorporating advanced modeling techniques to enhance resource allocation and decision-making in agricultural systems, aiming for a triple win in reducing GHG emissions, enhancing food security, and promoting economic sustainability. An integrated approach harnessing life cycle assessment, system dynamics model, and multi-objective optimization methodologies was employed to evaluate the effects, trade-offs, and synergies of resource allocation in the context of CSA practices. In Jiangxi Province, China, a case study demonstrated notable reductions in overall carbon footprints, ranging from 6.02 % to 12.03 %. Additionally, applying the Non-dominated Sorting Genetic Algorithm II optimization algorithm to the model led to significant enhancements, such as an 11.24 % increase in grain nutrient availability, a 20.99 % boost in economic returns, and a 19.36 % decrease in GHG emissions. The findings underscore the efficacy of optimizing resource allocation to attain economic, environmental, and social advantages and curb carbon emissions. Moreover, pivotal policy recommendations encompass land use transformation, optimal food production allocation, and bioenergy production restructuring. Enforcing the practices of CSA and integrating them with carbon market transactions are crucial for sustainable agricultural development. This innovative framework provides a sustainable global agricultural management model with a low-carbon footprint, which is particularly beneficial in resource-scarce regions with competing policy objectives.