Agricultural non-point source pollution refers to pollutant emissions from scattered pollution sources such as agricultural production activities and rural domestic sewage. It has a wide range of sources and is difficult to control centrally, which has become a major challenge in global water pollution governance. As an important surface water resource in western Yunnan Province, Erhai Lake has long been under pollution pressure from agricultural activities. Data shows that in 2007, agricultural sources contributed 40% of major water pollutants in China, and in recent years, the load of agricultural non-point source pollution has continued to rise. The population density in the Erhai Lake Basin is 256 people km⁻², and agricultural production is intertwined with domestic sewage discharge. How to accurately identify the contribution of different pollution sources has become the key to formulating effective pollution control strategies.
Recently, the team pf researchers led by Professor Wen Xu from China Agricultural University took the Haixi area of the Erhai Lake Basin as the research object. By integrating farmer surveys, literature materials and statistical data, they systematically quantified the emissions of four pollutants, namely ammonia nitrogen (NH₃-N), total nitrogen (TN), total phosphorus (TP) and chemical oxygen demand (COD), from agricultural production and rural domestic sewage in this area in 2022. The related paper has benn published in Frontiers of Agricultural Science and Engineering (DOI: 10.15302/J-FASE-2025622).
The research results show that the annual emissions of the four pollutants in the Haixi area in 2022 were 72.9 t of NH₃-N, 264.1 t of TN, 29.2 t of TP and 1453.3 t of COD, respectively. In terms of sources, rural domestic sewage was the main contributor to NH₃-N, accounting for 74%; crop production was the primary source of TN, accounting for 45%; and livestock and poultry breeding was the main source of TP and COD, accounting for 52% and 71%, respectively. Specifically, in terms of crop types, vegetables, corn and beans contributed most of the pollutant emissions in crop production. For livestock and poultry pollution, dairy cows and pigs were the main sources, among which the pollutant emissions from dairy cow breeding accounted for more than half of the total emissions from livestock and poultry.
In terms of spatial distribution, Shangguan Town has become a key area for the control of all pollutants. Its livestock and poultry breeding industry is developed, and the emissions of the four pollutants account for 21%–44% of the total area. In addition, Wanqiao Town has the largest crop planting area, making it the town with the highest crop pollution emissions; the southern towns are more significantly affected by domestic sewage. Although sewage collection systems have been laid, some pipelines are damaged, leading to untreated sewage directly flowing into the lake.
This study comprehensively quantifies the emissions of the four pollutants, making up for the limitation of traditional models that only focus on nitrogen and phosphorus. Through more than 300 farmer surveys and on-site sampling, combined with the Manual of the Second Pollution Census Correlation Coefficients, it realizes the localization and precision of pollution source data. It further refines to crop and livestock types, providing a scientific basis for targeted management and control.
These findings provide precise guidance for the governance of agricultural non-point source pollution in the Erhai Lake Basin. The research suggests that for livestock and poultry breeding in northern towns, comprehensive treatment technology of dairy cow manure and optimized feed formulas can be promoted; in crop growing areas in the central and northern regions, priority should be given to optimizing the planting structure of vegetables, corn and beans, and promoting low-pollution modes such as rice-fava beans rotation; southern towns need to strengthen the maintenance of sewage pipe networks to reduce the pipe damage rate. In addition, the research method can be used as a reference for pollution assessment in other lake basins, providing scientific support for the formulation of policies for agricultural green development and water quality protection.
DOI: 10.15302/J-FASE-2025622