Spatiotemporal Pattern and Driving Mechanism of Agricultural Non-Point Source Pollution: A Case Study of Inner Mongolia in 2002–2023

Agricultural non-point source pollution (ANPSP) represents a major threat to water quality, yet its spatiotemporal dynamics in arid and semi-arid regions remain poorly quantified. This study establishes an integrated assessment framework to analyze the spatiotemporal patterns and driving mechanisms of ANPSP in Inner Mongolia, China, from 2002 to 2023. Using a combination of inventory analysis, pollution load equivalence assessment, and the Tapio decoupling model, we systematically examined the evolution of four pollution sources—chemical fertilizers, livestock breeding, agricultural solid waste, and rural domestic discharge—across 12 administrative regions. These methods were sequentially applied to quantify loads, standardize impacts, and evaluate the economy–environment relationship, forming a coherent analytical chain. Key results indicate the following: (1) Pollutant loads increased consistently over the study period, with chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP) rising by 24.21%, 31.67%, and 31.14%, respectively, largely driven by livestock sector expansion. (2) Spatial distribution was highly heterogeneous, with Tongliao, Chifeng, and Hulunbuir contributing 50.58–58.31% of total emissions, in contrast to minimal impacts in western regions. (3) Decoupling analysis indicated variable environment–economy relations, where fertilizer use and grain output reached strong decoupling in 2010–2011 and 2018–2019, whereas livestock pollution exhibited more unstable decoupling trajectories. A cluster-derived risk zoning scheme identified Bayannur as the only high-risk area and highlighted the need for tailored management approaches in medium- and low-risk zones. This study offers a scientific foundation for targeted ANPSP mitigation and sustainable agricultural strategy formulation in ecologically vulnerable areas.