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Human-water harmony in the Yellow River Basin has an important influence on promoting ecological protection and high-quality development in the Yellow River Basin. This paper explores the degree of harmony between humans and water in the provinces of the Yellow River Basin. Based on the provincial-level data of nine provinces from 2001 to 2020, a human-water harmonious coupling coordination degree model was constructed, and the spatial and temporal analysis of the coupling coordination characteristics of nine provinces was carried out utilizing ArcGIS software. The results revealed that: (1) From the point of view of human-water harmony, from 2001 to 2020, China's human-water relationship was on the rise, from reluctant coupling coordination to good coupling coordination. (2) Qinghai, Gansu, and Sichuan provinces have the most significant increase in human-water harmony, from on the verge of a dysfunctional decline to quality coupling coordination. (3) From 2001 to 2011, the human system's comprehensive index was inferior to that of the water system's comprehensive index. In 2003, the comprehensive index of human and water systems was the largest. From 2012 to 2020, the human system's comprehensive index was higher than the water system. However, in 2015, the two indices diverged significantly HIGHLIGHTS A human-water harmony model was established to evaluate the human-water relationship in the Yellow River Basin.; The spatial and temporal analysis of human-water harmony in nine provinces in the last 20 years was carried out.; Put forward relevant suggestions according to the evaluation results.;

Summary: In response to escalating environmental concerns surrounding antibiotic pollution, the utilization of calcium-montmorillonite minerals for tetracycline wastewater treatment is gaining prominence. This study systematically analyzed the physicochemical properties of calcium-montmorillonite through scanning electron microscope, contact angle analysis, X-ray diffraction, and Fourier transform infrared spectroscopy. It explored the adsorption efficacy and mechanisms for tetracycline removal, considering factors like initial pH, adsorption duration, concentration, and co-cations (Na+ and Ca2+). Under optimized conditions, achieving over 90% tetracycline removal with a maximum adsorption capacity of 526 mg/g, the study revealed competitive adsorption sites for coexisting cations. The Langmuir model best described the monolayer adsorption process, while kinetic studies favored the pseudo-first-order model. This research offers comprehensive insights into tetracycline adsorption on calcium-montmorillonite, emphasizing its potential as an efficient, cost-effective adsorbent for pharmaceutical wastewater treatment.

Heavy metal pollution in water environment has always been a hot issue in environmental pollution research. Among various removal methods of heavy metal pollution, adsorption has attracted attention because of its low cost and low secondary pollution. Montmorillonite is one of an ideal adsorption materials because of its natural pore structure and a high specific surface area. In this review, the modification methods of montmorillonite are introduced. The adsorption effect of different heavy metal ions and the main factors affecting the adsorption are discussed in detail. Meanwhile, the adsorption mechanism is intensively reviewed. The removal of Cr(VI), Cd(II), Pb(II), Cu(II), Cs(I), Co(II), Hg(II), Zn(II), Ni(II), and other nine heavy metal ions by modified montmorillonite was summarized and discussed, and the optimal pH values for different adsorbents were also different, but they were all less than 7, and the removal rates of heavy metal ions by modified montmorillonite under optimal conditions were all greater than 90%. It is concluded that the composite montmorillonite material has a great adsorption potential. Finally, it is proposed that the combination of advanced oxidation and composite montmorillonite material adsorption to remove heavy metal ions is an important direction of adsorption and removal of heavy metal ions in the water environment in the future. HIGHLIGHTS Widely collected the domestic and foreign literature works on the modified adsorption of heavy metals by montmorillonite, and used the methods of analysis and synthesis to identify, classify, merge and study the original literature as a whole.; The promising modification direction of montmorillonite and the key points of in-depth research in the removal of heavy metals were put forward.;

As global warming progresses, forest fires have become more frequent, leading to the destruction of forest biodiversity and consequently affecting Earth’s ecosystems and human living conditions. The ability to predict the long-term trend of forest fires holds significant value for fire prevention and management. In Yunnan Province, China, a region rich in forest resources, this study utilized temperature, average annual rainfall, relative humidity, and wind speed data from 1991 to 2021. We forecasted forest fires using the stepwise regression and autoregressive integrated moving average (ARIMA) model, incorporating the collected forest fire data. The findings reveal a negative correlation between rainfall and forest fire incidence, whereas wind speed exhibited a positive correlation. The ARIMA model forecasts a cyclical trend in fires from 2022 to 2033, with considerable fluctuations in the number of fires, notably in 2027 and 2033. The projected affected area is anticipated to show a marked increase from 2028 onwards. This research not only provides a novel methodology for forecasting forest fires but also lays a scientific foundation for the development of future fire prevention and mitigation strategies.

As global climate change and human activities increasingly influence our world, forest fires have become more frequent, inflicting significant damage to ecosystems. This study conducted measurements of combustible materials (moisture content ratio, ignition point, and calorific value) across 14 representative sites. We employed Pearson correlation analysis to ascertain the significant differences in combustible properties and utilized entropy methods to evaluate the fire resistance of materials at these sites. Cluster analysis led to the development of four combustible models. Using BehavePlus software, we simulated their fire behaviors and investigated the effects of wind speed and slope on these behaviors through sensitivity analysis. The results revealed notable differences in the moisture content ratios among different types of combustibles, especially in sites 2, 3, 8, 9, and 13, indicating higher fire risks. It was also found that while humus has a higher ignition point and lower calorific value, making it less prone to ignite, the resultant fires could be highly damaging. The Pearson analysis underscored significant variations in the moisture content ratios among different combustibles, while the differences in ignition points and calorific values were not significant. Sites 5 and 6 demonstrated stronger fire resistance. The simulations indicated that fire-spread speed, fireline intensity, and flame length correlate with, and increase with, wind speed and slope. Sensitivity analysis confirmed the significant influence of these two environmental factors on fire behavior. This study provides critical insights into forest fire behavior, enhancing the capability to predict and manage forest fires. Our findings offer theoretical support for forest fire prediction and a scientific basis for fire management decision-making.