Manure is one of the main sources of heavy metal (HM) pollution on farmlands. It has become the focus of global ecological research because of its potential threat to human health and the sustainability of food systems. Soil pH and organic matter are improved by manure and play pivotal roles in determining soil HM behavior. Geochemical modeling has been widely used to assess and predict the behavior of soil HMs; however, there remains a research gap in manure applications. In this study, a geochemical model (LeachXS) coupled with a pH-dependent leaching test with continuously simulations over a broad pH range was used to determine the effects and pollution risks of pig or cattle manure separate application on soil HMs distribution. Both pig and cattle manure applications led to soil pH reduction in alkaline soils and increased organic matter content. Pig manure application resulted in a potential 90.5-156.0 % increase in soil HM content. Cattle manure did not cause significant HM contamination. The leaching trend of soil HMs across treatments exhibited a V-shaped change, with the lowest concentration at pH = 7, gradually increasing toward strong acids and bases. The dissolved organic matter-bound HM content directly increased the HM availability, especially for Cu (up to 8.4 %) after pig manure application. However, more HMs (Cr, Cu, Zn, Ni) were in the particulate organic matter-bound state than in other solid phases (e.g., Fe-Al(hydr) oxides, clay minerals), which inhibited the HMs leaching by more than 19.3 % after cattle manure application. Despite these variations, high HM concentrations introduced by pig manure raised the soil contamination risk, potentially exceeding 40 times at pH ±1. When manure is returned to the field, reducing its HM content and mitigating possible pollution is necessary to realize the healthy and sustainable development of circular agriculture.

Agricultural straw waste and livestock manure are often misplaced resources. The separation of planting and breeding has induced significant pressure on the environment. Thus, there is a growing need for a system that can integrate crop and livestock farming to improve resource efficiency. To clarify the current state of crop–livestock systems in China and elsewhere, a bibliometric analysis was conducted for a total of 18,628 published English and 3460 published Chinese research articles and dissertations on circular agriculture. The published research papers were taken from the ISI Web of Science and CNKI database to explore research hotpots, research methods, theme trends, and mainstream technical models of crop–livestock systems from 1981 to 2021. Recent progress in crop–livestock systems was analyzed from ecological, economic, social benefits, and stakeholder perspectives. The research results showed that compared with traditional agricultural models, crop–livestock systems had far more ecologic and social benefits, including gaining higher net income and input-output ratio, improving soil quality, and mitigating global warming. The drivers of crop–livestock systems’ development were also analyzed from stakeholders’ perspectives. The study provides insights into the development of circular agriculture by reducing the pollution risks of agricultural waste and improving both ecological and economic benefits of the system.

With the rapid development of circular agriculture in China, balancing agricultural income and environmental impact by adjusting the structure and scale of circular agriculture is becoming increasingly important. Agriculture is a major source of greenhouse gas and income earned from agriculture drives sustainable agricultural development. This paper built a multi-objective linear programming model based on greenhouse gas emission and agricultural product income and then optimized the structure and scale of circular agriculture using Beiqiu Farm as a case study. Results showed that greenhouse gas emission was mainly from manure management in livestock industry. While the agriculture income increased by 64% after optimization, GHG emission increased by only 12.3%. The optimization made full use of straw, manure and fodder, but also minimized soil nitrogen loss. The results laid a generalized guide for adjusting the structure and scale of the planting and raising industry. Measures for optimizing the management of manure were critical in achieving low agricultural carbon emissions in future agricultural development efforts.

Freshwater resources are becoming increasingly scarce in coastal areas, limiting crop productivity in coastal farmlands. Although the characteristic of crop water use is an important factor for water conservation in coastal farmlands, it has not been studied extensively. This study aimed to depict the water use process of soil–plant systems under saline stress in coastal ecosystems and optimize water management. An intensive observation experiment was performed within China’s Yellow River Delta to identify the water use processes and crop coefficients (K_C) and also quantify the impacts of salt stress on crop water use. The results show that shallow groundwater did not contribute to soil water in the whole rotation; K_C values for wheat–maize, wheat–sorghum, and wheat–soybean rotation systems were 45.0, 58.4, and 57% less, respectively, than the FAO values. The water use efficiency of the maize (8.70) and sorghum (9.00) in coastal farmlands was higher than that of the soybean (4.37). By identifying the critical periods of water and salt stress, this paper provides suggestions for water-saving and salinity control in coastal farmlands. Our findings can inform the sustainable development of coastal farmlands and provide new insights to cope with aspects of the global food crisis.

Sloping farmland erosion in cold-region black soil zones threatens global agriculture, yet regional-scale quantitative evidence on the erosion mitigation performance and spatial suitability of control measures remains lacking. This study integrated 959 field observation datasets from 132 peer-reviewed publications, and used meta-analysis and Boosted Regression Tree (BRT) models to evaluate tillage, biological, engineering, and combined conservation measures in Northeast China. Results showed that all measures significantly reduced erosion, achieving an average runoff reduction of 73.2% and sediment reduction of 83.6%. Specifically, engineering measures showed the highest runoff reduction, while combined measures achieved more than 95% sediment reduction. Machine learning revealed that runoff reduction was primarily regulated by precipitation, whereas sediment reduction was mainly controlled by soil clay content and bulk density. Spatially, tillage, biological, and engineering measures showed the highest suitability in continuous cultivated plains, plain–hill transition zones, and low hilly and gully regions, respectively. This study moves erosion-control assessment beyond comparisons of average runoff and sediment reduction rates toward environmentally matched spatial allocation, providing a basis for targeted black soil conservation and resilient grain production in cold-region agricultural landscapes.