Human activities, global warming, frequent extreme weather events, and changes in atmospheric composition affect the solar radiation reaching the Earth’s surface, affect mass and heat transfer at the air–water interface, and induce oscillations in wind-driven internal waves. This leads to changes in the spatiotemporal characteristics of thermal stratification in lakes, altering lake circulation patterns and vertical mass transfer. However, thermal stratification structures are often overlooked. The intensification of lake thermal stratification due to warming may lead to increased release of bottom pollutants, spreading through the dynamic behavior of the thermocline to the epilimnion. Moreover, the increased heat storage is beneficial for the growth and development of certain phytoplankton, resulting in rapid transitions of the original steady state of lakes. Consequently, water quality deterioration, ecological degradation, and declining biodiversity may occur. Conventional surface water monitoring may not provide comprehensive, accurate, and timely assessments. Model simulations can better predict future thermal stratification behaviors, reducing financial burdens, providing more refined assessments, and thus preventing subsequent environmental issues.

Water quality estimation tools based on real-time monitoring are essential for the effective management of organic pollution in watersheds. This study aims to monitor changes in the levels of chemical oxygen demand (COD, CODMn) and dissolved organic matter (DOM) in Erhai Lake Basin, exploring their relationships and the ability of DOM to estimate COD and CODMn. Excitation emission matrix–parallel factor analysis (EEM–PARAFAC) of DOM identified protein-like component (C1) and humic-like components (C2, C3, C4). Combined with random forest (RF), maximum fluorescence intensity (Fmax) values of components were selected as estimation parameters to establish models. Results proved that the COD of rivers was more sensitive to the reduction in C1 and C2, while CODMn was more sensitive to C4. The DOM of Erhai Lake thrived by internal sources, and the relationship between COD, CODMn, and DOM of Erhai Lake was more complicated than rivers (inflow rivers of Erhai Lake). Models for rivers achieved good estimations, and by adding dissolved oxygen and water temperature, the estimation ability of COD models for Erhai Lake was significantly improved. This study demonstrates that DOM-based machine learning can be used as an alternative tool for real-time monitoring of organic pollution and deepening the understanding of the relationship between COD, CODMn, and DOM, and provide a scientific basis for water quality management.

The environmental distribution and migration of bisphenol A (BPA) has attracted attention due to its widespread use. The Erhai Lake Basin is dominated by agricultural production and tourism, and almost no industry. In this research, BPA pollution in the non-industrial region was investigated. BPA was found in all samples of inflow rivers, with concentrations ranging 2.80 ng/L~61.85 ng/L. The measured 15 rivers that account for 78.7% of the total inflow volume were inputting BPA concentration of 20.69 ng/L into Erhai Lake with an annual load of 8.54 kg/year. The measured BPA removal efficiency of sewage treatment plants ranged 49.8%~92.8%. Oxidation Ditch and A2O-MBR treatment process achieved the better BPA removal efficiency. The amount of BPA discharged directly to Erhai Lake from the effluent of the sewage plants each year was 1.63 kg. Based on the above research, a multimedia model of QWASI was established, and water concentration calculated was 0.203ng/L. A PNEC value considering more sensitive receptors was applied to this study, and it was indicated that there was a certain ecological risk in the water of the Boluo River estuary, while other rivers and lake were relatively safe. It was revealed that the ecological risk of BPA was relatively low in the Erhai Lake.

Steroid estrogens (SEs) are mainly derived from livestock manure, and composting is the common method of bioresource utilization. In this study, an open-air composting experiment with dairy manure was conducted to observe the degradation and loss of five SEs under the influence of different precipitation intensities and additional mixed fermentation strains. SE determination results for dairy manure after 30 days of composting indicated that the average removal rates of 17α-estradiol (E2α), estrone (E1), 17β-estradiol (E2β), 17α-ethinyl estradiol (EE2), estriol (E3), and estradiol equivalent (EEQ) were 76.67%, 71.07%, 73.88%, 92.02%, 98.77%, and 88.11%, respectively, partly due to SE runoff. The rates of SEs leaching from the open-air composting dairy manure ranged from 0.05% to 4.75% after 10 rounds of 5–60 mm/d simulated rainfall. The total leaching amount of SEs was positively correlated with rainfall, but the leaching concentrations of SEs were just the opposite. As a result of its role as a degradation intermediate of other SEs, E3 was the most prone to run off. By strengthening the action of microorganisms, the total leaching amount of EEQ increased by 5%, E3 increased by five times, and E2β also underwent a transition from a conjugated form to free. However, there were also fewer final SEs remaining in the composted product, as well as the environmental risks of conjugated SEs. These conclusions can provide beneficial suggestions and references for controlling the environmental risks of SEs in the process of composting livestock and poultry manure.

Steroid estrogens (SEs) play a significant role as endocrine-disrupting substances, and one of their major sources is animal manure. However, there is limited information available regarding the loss of SEs in farmland soil after the application of commercial composted animal manure or fertilizers. To address this gap, our study aimed to simulate rainfall and flood irrigation scenarios and investigate the loss characteristics of SEs, as well as Chemical Oxygen Demand (COD), Total Nitrogen (TN), and Total Phosphorus (TP) in runoff from soil–manure mixtures. The results demonstrated that the loss concentrations of SEs (73.1 ng/L of the mean E2β active equivalent factor) presented a potential environmental risk. Additionally, substituting composted manure with commercial organic fertilizers lead to a significant reduction in TP (maximum 56%) and TN (maximum 24%) loss. Consequently, the application of commercial organic fertilizers offers considerable advantages in maintaining nitrogen and phosphorus fertilization efficiency while controlling SEs loss. Furthermore, our study explored the synergistic pollution mechanism among these pollutants and observed significant correlations between SEs and TN, TP, and COD loss concentrations, indicating the simultaneous occurrence and migration of these pollutants in agricultural non-point source pollution. These results provide valuable insights into the environmental risk associated with SEs from agricultural non-point sources.