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During the large-scale vegetation restoration on the Loess Plateau, the introduction of exotic species with high water consumption, such as Robinia pseudoacacia L., led to widespread soil desiccation, and resulted in severe drought stress and increasing risk of forest degradation and mortality. Accurate assessment of drought-induced mortality risk in plantation forests is essential for evaluating and enhancing the sustainability of ecological restoration, yet quantitative research at the regional scale on the Loess Plateau is lacking. With a focus on Robinia pseudoacacia L. plantations, we utilized a coupled model of the Biome BioGeochemical Cycles model and plant supply–demand hydraulic model (BBGC-SPERRY model) to simulate the dynamics of the annual average percentage loss of whole-plant hydraulic conductance (APLK) at 124 meteorological stations over an extended period (1961–2020) to examine changes in plant hydraulic safety in Robinia pseudoacacia L. plantations. Based on the probability distribution of APLK at each site, the drought-induced mortality risk probability (DMRP) in Robinia pseudoacacia L. was determined. The results indicate the BBGC-SPERRY model could effectively simulate the spatiotemporal variations in transpiration and evapotranspiration in Robinia pseudoacacia L. stands on the Loess Plateau. The mean APLK and DMRP exhibited increasing trends from southeast to northwest along a precipitation gradient, with their spatial patterns on the Loess Plateau mainly driven by mean annual precipitation and also significantly influenced by other climatic and soil factors. The low-risk (DMRP < 2%), moderate-risk (2% ≤ DMRP ≤ 5%), and high-risk (DMRP > 5%) zones for drought-induced mortality in Robinia pseudoacacia L. accounted for 60.0%, 30.7%, and 9.3% of the study area, respectively. These quantitative findings can provide an important basis for rational forestation and sustainable vegetation management on the Loess Plateau. [ABSTRACT FROM AUTHOR]

In this study, based on the shear-stress transport κ–ω turbulent model, the improved delayed detached eddy simulation method has been used to simulate the unsteady aerodynamic performance of trains with different obstacle deflectors at two yaw angles (0° and 15°). The numerical algorithm is used and some of the numerical results are verified through wind tunnel tests. By comparing and analysing the obtained results, the effects of the obstacle deflectors on the force of the trains as well as the pressure and flow structure around the trains are elucidated. The results show that the obstacle deflectors primarily affect the flow field at the bottom of the head car as well as the wake flow, and that the internal oblique-type obstacle deflector (IOOD) markedly improves the aerodynamic performance of the trains, by decreasing most of the aerodynamic forces of the train cars and minimising their fluctuations. Further, a nonzero yaw angle weakens or even changes the effect of the IOOD on the aerodynamic forces of the train cars. However, the effect of the IOOD is more on the tail car. [ABSTRACT FROM AUTHOR]

By using numerical calculation method, 2-car high-speed train going through the station or intersecting at the station at the different speed was simulated. The bow lift change, influence of pantograph state and barrier door on pantograph lift change was researched. Results indicate that, during the train coming into the platform or going out of it, the fluctuation of pantograph lift is significant. When the train going through the platform, lift change of pantograph bow and upper frame is the biggest. There is a linear relationship between pantograph bow and the power of speed, and the law is not changed by pantograph state. Lift change of pantograph bow in the state of adverse pantograph is greater than it in the state of favorable pantograph, and influence of barrier door on the pantograph lift change is limited. When two trains are passing each other through the platform, distribution of lift change of pantograph components and law of lift change with train speed are changed significantly by pantograph state. Influence of barrier door on the pantograph lift change is more obvious than one of the train going through platform. The meeting position in the station has no effect on the lift change of pantograph. Lift change of pantograph is affected obviously by non-uniformity of train passing. [ABSTRACT FROM AUTHOR]

Clarifying the regional transmission and local generation contributions of ozone （O 3 ） is important for controlling O 3 pollution. To quantify the regional background and spatial-temporal variations of O 3 , a comprehensive study was conducted using multiple methods including principal component analysis （PCA） and TCEQ, with Henan Province as a case study. Based on monitoring data from 59 national sites in Henan Province during 2019-2021, four methods were employed to estimate the regional background of O 3 . Method 1 was the traditional method, performing O 3 univariate-multisite PCA analysis. Method 2 was a multivariate-single-site PCA analysis considering nitrogen dioxide and meteorological conditions as constraints. Method 3 combined PCA and multiple linear regression （MLR） to determine regional background contributions, drawing on the idea of source apportionment. Method 4 was the TCEQ method that used the lowest measured O 3 -8h concentration as the regional background. The estimation results showed that Methods 1 and 2 were basically equal, and Methods 3 and 4 were approximately 37-60 μg·m -3 lower than Method 1. From 2019 to 2021, the changes in regional background ρ （O 3 -8h） estimated by Methods 1-4 were 1.6, -13.4, 5.9, and -3.5 μg·m -3 , respectively. The average estimations derived from multiple methods showed that the regional background ρ （O 3 -8h） in Henan Province from 2019 to 2021 concentrations were 82.0, 79.0, and 79.7 μg·m -3 , accounting for 75.9%, 76.4%, and 78.7% of the total regional O 3 -8h, respectively. The regional background O 3 -8h estimated by the four methods showed obvious seasonal changes, characterized by summer &gt; spring &gt; fall &gt; winter.

The spatial-temporal distribution pattern of surface O 3 over the Qinghai-Xizang Plateau （QXP） was analyzed based on air quality monitoring data and meteorological data from 12 cities on the QXP from 2015 to 2021. Kolmogorov-Zurbenko （KZ） filtering was employed to separate the original O 3 -8h series into components at different time scales. Then, multiple linear regression of meteorological variables was used to quantitatively isolate the effects of meteorology and emissions. The results revealed that the annual mass concentrations of surface O 3 -8h from 2015 to 2021 in 12 cities over the QXP ranged from 78.7 to 156.7 μg·m -3 , and the exceedance rates of O 3 mass concentrations （National Air Quality Standard of grade II） ranged from 0.7%-1.5%. The monthly O 3 -8h mass concentration displayed a single-peak inverted "V"-shape and a multi-peak "M"-shape. The maximum monthly concentration of O 3 occurred in April to July, and valleys occurred in July, September, and December. The short-term, seasonal, and long-term components of O 3 -8hdecomposed by KZ filtering contributed 29.6%, 51.4%, and 9.1% to the total variance in the original O 3 sequence in 12 cities, respectively. From the whole region, the meteorological conditions were unfavorable for O 3 reduction on the QXP from 2015 to 2017, which made the long-term component of O 3 increase by 0.2-2.1 μg·m -3 . The meteorological conditions were favorable for O 3 -8h reduction from 2018 to 2021, which led to the long-term component of O 3 -8h decrease by 0.4-1.1 μg·m -3 . The meteorological conditions increased the long-term component of O 3 -8h in Ngari, Lhasa, Naqu, Nyingchi, Qamdo, Haixi, and Xining, with an average contribution of 30.1%. The meteorological conditions decreased the long-term component of O 3 -8h in Shigatse and Golog, with contributions of 359.0% and 56.5%, respectively. The increase in the long-term component of O 3 -8h in Ngari, Shigatse, Nagqu, Haixi, and Xining could be due to the rapid decrease in the long-term component of PM 2.5 （4.04 μg·（m 3 ·a） -1 ）.

With the rapid development of remote sensing technology, research on land use classification methods based on hyperspectral remote sensing images has attracted widespread attention. Existing land-use classification studies mostly use the average filtering method at a single scale for spectral image processing. These methods cannot accurately filter the window range, which leads to the neglect of image detail information, and the single kernel matrix cannot characterize multifeature information, resulting in reduced classification accuracy. Therefore, this study intended to use a superpixel segmentation method to perform multiscale superpixel segmentation on the first principal component of a hyperspectral image at multiple scales. By combining the weighted multiscale spatial-spectral kernel and the original spatial-spectral kernel to form a synthetic kernel for land use classification, the hyperspectral image of the National Mall in Washington DC was used as experimental data to test and analyze this method. The experimental results showed that the classification accuracy of this method on the experimental test set was 98.53%, which is compared with the classification results obtained by the single-scale spatial spectral synthetic nuclear method, the original spatial spectral synthetic nuclear method and the wavelength segmented synthetic nuclear method, the effective classification accuracy with this method was increased by 7.56%. The results prove that this method can effectively solve the problems of the lack of adaptability of the image spectrum and the lack of comprehensive spectral information and can significantly improve the accuracy of land use classification.