53 research outputs found

    Global cropland nitrous oxide emissions in fallow period are comparable to growing-season emissions

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    This study was supported by the Youth Innovation Program of Chinese Academy of Agricultural Sciences (No. Y2023QC02), the National Natural Science Foundation of China (42225102, 42301059, 32172129, 42207378), the National Key Research and Development Program of China (2021YFD1700801, 2022YFD2300400), Technology Research System-Green manure (Grant No. CARS-22-G-16).Peer reviewedPostprin

    Anthropogenic N input increases global warming potential by awakening the ‚Äúsleeping‚ÄĚ ancient C in deep critical zones

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    Even a small net increase in soil organic carbon (SOC) mineralization will cause a substantial increase in the atmospheric CO2 concentration. It is widely recognized that the SOC mineralization within deep critical zones (2 to 12 m depth) is slower and much less influenced by anthropogenic disturbance when compared to that of surface soil. Here, we showed that 20 years of nitrogen (N) fertilization enriched a deep critical zone with nitrate, almost doubling the SOC mineralization rate. This result was supported by corresponding increases in the expressions of functional genes typical of recalcitrant SOC degradation and enzyme activities. The CO2 released and the SOC had a similar 14C age (6000 to 10,000 years before the present). Our results indicate that N fertilization of crops may enhance CO2 emissions from deep critical zones to the atmosphere through a previously disregarded mechanism. This provides another reason for markedly improving N management in fertilized agricultural soils

    Effect of landscape pattern on river water quality under different regional delineation methods: A case study of Northwest Section of the Yellow River in China

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    Study region: A typical arid irrigation area of the Yellow River, Ningxia, Northwest China. Study focus: At present, few studies have evaluated the effects of nested watershed and runoff process on the relationships between landscape patterns and water quality. In this study, we aimed to quantify the relationships between landscape pattern and river water quality using two delineation methods. One method involved a water quality monitoring site only corresponding only to its own sub-watershed, while the other method involved a water quality monitoring site corresponding to all of its upstream sub-watersheds. New hydrological insights for the region: We collected water quality monitoring data, including DO, CODMn, NH3-N, TP, TN, pH for the irrigation period (May, 2021 ‚Äď August, 2021) and the non-irrigation period (December, 2021 ‚Äď March, 2022) for seven sub-watersheds. Our results revealed that when a water quality monitoring site corresponded to all the sub-basins involved in the runoff process, the correlations between landscape composition and water quality parameters were stronger. Additionally, the degree to which landscape configuration explained the overall water quality was greater in such cases. We also found that the buffer zone scale accounted for more than 97.3% of the overall water quality variation. These results highlight the importance of aligning water quality monitoring sites with the corresponding sub-watersheds and emphasize the significance of land-use management in the riparian scale near the Yellow River for water quality protection

    Adaptability analysis and model development of various LS-factor formulas in RUSLE model: A case study of Fengyu River Watershed, China

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    The slope length and slope steepness factor (LS-factor) formula in the Revised Universal Soil Loss Equation (RUSLE) has a considerable level of uncertainty due to the existence of multiple methods. In this study, four commonly used formulas for the slope length factor and two formulas for the slope gradient factor were chosen and combined based on their applicability to the specific research context. Based on the ModelBuilder in ArcGIS Pro 3.0, a RUSLE calculation model (RUSLE-Cal model) was constructed in the study, which can automatically calculate the soil erosion modulus using four commonly used RUSLE formulas and one combination formula. Taking the Fengyu River watershed in China as a case study, this research analyzes the uncertainty of different LS-factor formulas and validates the accuracy of RUSLE simulation results using measured sediment data. The optimal combination of LS-factor formulas is selected, and an in-depth analysis is conducted on the origins and suitability of each formula. The accuracy validation results indicate that, for the Fengyu River watershed, the optimal combination of L-factor and S-factor formulas were determined based on the slope gradient. Specifically, L1 formula was used when slope¬†‚ȧ¬†10¬į, and L3 formula was used when slope¬†greater than¬†10¬į. Similarly, S1 formula was used when slope¬†‚ȧ¬†18¬į, and S2 formula was used when slope¬†greater than¬†18¬į. The RUSLE model achieved the best simulation results with a relative error of 5.55%. The results of the uncertainty analysis indicate that the four formulas have a significant impact on the simulated soil erosion, with a RE ranging from ‚ąí99.18% to 31.49%. Therefore, based on literature review and formula analysis, a suitability selection table for L-factor and S-factor formulas is provided, which can provide formula basis for the improvement of soil erosion in watershed models

    Dataset for "A novel injection technique: using a field-based quantum cascade laser for the analysis of gas samples derived from static chambers"

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    Dataset for "A novel injection technique: using a field-based quantum cascade laser for the analysis of gas samples derived from static chambers

    Study on the Relationship between Root Metal Flow Behavior and Root Flaw Formation of a 2024 Aluminum Alloy Joint in Friction Stir Welding by a Multiphysics Field Model

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    In friction stir welding (FSW), many defects (such as kissing bond, incomplete penetration, and weak connection) easily occur at the root of the welded joint. Based on the Levy–Mises yield criterion of the Zener–Hollomon thermoplastic constitutive equation, a 3D thermal–mechanical coupled finite element model was established. The material flow behavior and the stress field at the root area of a 6 mm thick 2024-T3 aluminum alloy FSW joint were studied. The influence of pin length on the root flaw was investigated, and the formation mechanism of the “S line” defects and non-penetration defects were revealed. The research results showed that the “S line” defect forms near the bottom surface of the pin owing to the insufficiently mixed material from the advancing side (AS) and retreating side (RS) near the weld center. The non-penetration defect forms near the bottom surface of the workpiece owing to the insufficient driving force to make the material flow through the weld center. With the continual increase of pin length, the size of the “S line” defect and non-penetration defect reduces, and finally, the defect-free welded joint can be obtained with an optimized suitable length of the pin in this case

    CN-China: Revised runoff curve number by using rainfall-runoff events data in China

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    The curve number (CN) method developed by the United States Department of Agriculture (USDA) in 1954 is the most common adopted method to estimate surface runoff. For years, applicability of the CN method is a conundrum when implementing to other countries. Specifically, countries with more complex natural environment may require more dedicated adjustments. Therefore, the current CN look-up table provided by USDA might not be appropriate and could be questionable to be applied directly to regions elsewhere. Some studies have been conducted to modify CN values according to specified natural characteristics in scattered regions of mainland China. However, an integral and representative work is still not available to address potential concerns in general matters. In this study, a large set of rainfall-runoff monitoring data were collected to adjust CN values in 55 study sites across China. The results showed that the revised CN values are largely different from CN look-up table provided by USDA, which would lead to huge errors in runoff estimation. In this study, the revised CN (dubbed CN-China) provides better reference guidelines that are suitable for most natural conditions in China. In addition, scientists and engineers from other parts of the world can take advantage of the proposed work to enhance the quality of future programs related to surface runoff estimation
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