How to break the dilemma of agricultural non-point source pollution?

With global population growth and rising food demand, agriculture ensures food supply while bringing severe environmental problems. Among these, agricultural non-point source pollution (ANPSP) has become one of the major factors affecting water health and ecological security. ANPSP mainly refers to pollutants such as chemical fertilizers, pesticides, and livestock manure entering water bodies through runoff formed by rainfall or irrigation during agricultural production. Due to its dispersed sources and complex paths, it is far more difficult to control than industrial point source pollution. Against this backdrop, agricultural green development (AGD) has emerged as a key pathway to promote the sustainable transformation of agriculture. However, can we effectively control non-point source pollution and achieve a shift from a “high-input, high-emission” agricultural model to a “green and efficient” one?

Researcher Yonghong Wu from the Institute of Soil Science, Chinese Academy of Sciences and his colleagues, have systematically summarized the current status, challenges, and control strategies of ANPSP. The study points out that 30%−50% of the Earth’s surface is affected by ANPSP, with excessive input of nutrients such as nitrogen (N) and phosphorus (P) being the main cause of water eutrophication. In China, although the use of chemical fertilizers and pesticides has decreased since 2015, the problem of ANPSP remains severe, especially in agriculturally intensive regions such as the Yangtze River basin. The relevant paper has been published in Frontiers of Agricultural Science and Engineering (DOI: 10.15302/J-FASE-2025650).

The control of ANPSP faces three major challenges. Firstly, it is difficult to accurately trace pollution sources. Pollutants have diverse migration paths, including surface runoff, soil leaching, and even atmospheric deposition. Existing tracing methods such as isotopic labeling and hydrological models have their own limitations and cannot fully capture the spatiotemporal changes of pollution. Secondly, there is a lack of systematic integration between control technologies. Although individual technologies such as ecological interception ditches, constructed wetlands, and biogas projects already exist, they are unable to achieve synergistic control of multiple pollutants and nutrient recycling. Thirdly, the efficiency of large-scale regional control is low. Due to spatial differences in soil types, climatic conditions, and cropping patterns, uniform control measures are often ineffective. Additionally, high cross-regional coordination costs and insufficient coverage of monitoring stations limit the effectiveness of control efforts.

To address these challenges, researchers propose establishing a control system combining precise tracing, systematic integration, and intelligent regulation. In terms of precise tracing, artificial intelligence (AI), remote sensing, and sensor technologies can be integrated to build a pollution monitoring network, enabling the identification and early warning of pollutant sources and paths. For technology integration, the "4R" systematic strategy—Reduction at source, Retention in process, Reuse of nutrients, and Restoration of aquatic ecosystems—should be promoted to form a full-process control from farmland to water bodies. For example, in a demonstration project in the Taihu Lake region, this strategy achieved a 31%−54% reduction in N loss and a 25%−53% reduction in P loss.

Advanced technologies such as AI are expected to become supportive tools for promoting ANPSP control. By integrating machine learning, blockchain, and the Internet of Things (IoT), a pollution tracing and decision support platform can be established to assist in the precise management of fertilization, irrigation, and pesticide application, thereby reducing pollutant emissions at the source. Furthermore, the development of portable detection devices will help lower the threshold for small and medium-sized farmers to adopt pollution control measures.

In addition to technical means, policy guidance and international cooperation are equally important. The study suggests incorporating AGD indicators into local performance evaluation systems and incentivizing farmers to adopt green production methods through fiscal subsidies. Meanwhile, China can learn from the experiences of other developed countries in precision agriculture and emission monitoring, and share feasible ANPSP control solutions through international cooperation mechanisms.

The control of ANPSP is not only related to water quality security but also an important part of realizing agricultural green transformation and the United Nations Sustainable Development Goals (SDGs). In the future, through the joint promotion of technology, policies, and global collaboration, agriculture is expected to transform from a consumer of ecosystems to a restorer and value creator.