Distribution, sources and health risk assessment of polycyclic aromatic hydrocarbons in urban soils under different landform conditions of Taiyuan, China

Public concern about polycyclic aromatic hydrocarbons (PAHs) is rising due to their potential carcinogenic, teratogenic, and mutagenic effects. This study assessed PAHs in Taiyuan City’s plain and mountain soil, investigating concentrations, distribution, sources, and carcinogenic risk. Σ21PAHs concentrations in plain topsoil ranged from 133.2 to 6,410.6 ng/g (mean 1,444.7 ng/g), and in mountain soil from 66.5 to 2,250.2 ng/g (mean 585.5 ng/g). Approximately 55.1% of plain and 19.0% of mountain soil samples had contamination levels exceeding 600 ng/g. In plain soil, 4-ring and 5-ring PAHs dominated, while 2-ring and 3-ring PAHs were prevalent in mountain soil. Polluted areas in Taiyuan were primarily centered in the central-north, with higher content closer to industrial or business districts. PAH isomer ratios and principal component analysis/multiple linear regression (PCA/MLR) indicated coal combustion as the main PAH source, followed by coke production, vehicle emissions, and biomass combustion. Incremental lifetime cancer risks (ILCRs) showed Taiyuan’s PAH-related cancer risks were generally low, though heavily contaminated areas exhibited moderate risks. Plain regions had three times higher cancer risk than mountains, with children facing higher risk than adults. These findings highlight the need to consider PAH pollution while enhancing urban environmental quality

Grain size characteristics of the sand silt layers in the ancient delta of the dried Lop Nur lake (east Tarim Basin) and their environmental implications

Grain size characteristics of sediments are an effective index for the depositional environment. However, whether grain size is an accurate indicator for the formation environment is still obscure. In this study, two main types of lithology can be found in the yardang sediments from the Loulan area (Lop Nur): sand-silt layers and clay-silt layers. These two types are common in arid northwestern China. The clay-silt layers were primarily composed of lacustrine-swamp deposits, whereas the sand silt layers were formed under fluvial conditions based on geomorphic and stratigraphic lithologic evidence. However, grain size characteristics of the sand-silt layers, such as grain size distribution, C-M diagram, and grain size parameters, were consistent with that of the aeolian deposits. The study of the field deposition environment indicated that the sand-silt layers were fluvial sediments of materials originating from the aeolian sediments transported over a short distance and deposited by floods. As a result, the fluvial sediments exhibited the grain size characteristics of aeolian sediments. This indicates that some sediments may retain different depositional environment information, having undergone transportation and deposition processes. Therefore, when using grain size characteristics to determine the depositional environment, field deposition environment investigation should be combined with other environmental proxy indicators

Dynamics of NDVI and its influencing factors in the Chinese Loess Plateau during 2002–2018

Understanding the spatio-temporal changes of vegetation and its climatic control factors can provide an important theoretical basis for the protection and restoration of eco-environments. In this study, we analyzed the normalized difference vegetation index (NDVI) in the Chinese Loess Plateau (CLP) from 2002 to 2018 via trend analysis, stability analysis, and Mann-Kendall mutation test to investigate the change of vegetation. In addition, we also used the skewness analysis and correlation analysis to explore the contribution of climate change and human activities on regional vegetation changes. The results indicated that the overall increasing trend of NDVI from 2002 to 2018 was significant. The areas showing increased NDVI were mainly distributed in the southeastern CLP and the irrigation districts of the Yellow River to the north and west of the CLP, while the areas showing decreased NDVI were concentrated in the desert of the western Ordos Plateau, Longzhong Loess Plateau, and the built-up and adjacent areas. Precipitation was the dominant factor contributing to vegetation growth in the CLP, while vegetation was less dependent on precipitation in the irrigation districts. The increasement of NDVI has led to a prolonged response time of vegetation to water stress and a lag effect of less than two months in the CLP. The effect of temperature on NDVI was not significant; significant negative correlations between NDVI and temperature were found only in the desert, the Guanzhong Plain, the southern Liupan Mountains, and the southeastern Taihang Mountains, owing to high temperatures, urban heat islands, and large cloud cover in mountainous areas. Affected by the “Grain for Green Program” (GGP), NDVI in the CLP increased from 2002 to 2018; however, the increasing trends of NDVI for different vegetation cover types were significantly different owing to the difference in background status. The increasing contribution rate of NDVI in the CLP mainly came from crops and steppes. Urban not only led to the destruction of vegetation but also had radiation effect causing negative impact of NDVI around the cities. This resulted in the aggravation of the negative bias of NDVI with time in the CLP. The results provide a long-term perspective for regional vegetation protection and utilization in the CLP

Study on Spatial and Temporal Characteristics of Surface Albedo at the Northern Edge of the Badain Jaran Desert Based on C + STNLFFM Model

Obtaining surface albedo data with high spatial and temporal resolution is essential for measuring the factors, effects, and change mechanisms of regional land-atmosphere interactions in deserts. In order to obtain surface albedo data with higher accuracy and better applicability in deserts, we used MODIS and OLI as data sources, and calculated the daily surface albedo data, with a spatial resolution of 30 m, of Guaizi Lake at the northern edge of the Badain Jaran Desert in 2016, using the Spatial and Temporal Non-Local Filter-based Fusion Model (STNLFFM) and topographical correction model (C model). We then compared the results of STNLFFM and C + STNLFFM for fusion accuracy, and for spatial and temporal distribution differences in surface albedo over different underlying surfaces. The results indicated that, compared with STNLFFM surface albedo and MODIS surface albedo, the relative error of C + STNLFFM surface albedo decreased by 2.34% and 3.57%, respectively. C + STNLFFM can improve poor applicability of MODIS in winter, and better responds to the changes in the measured value over a short time range. After the correction of the C model, the spatial difference in surface albedo over different underlying surfaces was enhanced, and the spatial differences in surface albedo between shifting dunes and semi-shifting dunes, fixed dunes and saline-alkali land, and the Gobi and saline-alkali land were significant. C + STNLFFM maintained the spatial and temporal distribution characteristics of STNLFFM surface albedo, but the increase in regional aerosol concentration and thickness caused by frequent dust storms weakened the spatial difference in surface albedo over different underlying surfaces in March, which led to the overcorrection of the C model

Distribution Prediction of Strategic Flight Delays via Machine Learning Methods

Predicting flight delays has been a major research topic in the past few decades. Various machine learning algorithms have been used to predict flight delays in short-range horizons (e.g., a few hours or days prior to operation). Airlines have to develop flight schedules several months in advance; thus, predicting flight delays at the strategic stage is critical for airport slot allocation and airlines’ operation. However, less work has been dedicated to predicting flight delays at the strategic phase. This paper proposes machine learning methods to predict the distributions of delays. Three metrics are developed to evaluate the performance of the algorithms. Empirical data from Guangzhou Baiyun International Airport are used to validate the methods. Computational results show that the prediction accuracy of departure delay at the 0.65 confidence level and the arrival delay at the 0.50 confidence level can reach 0.80 without the input of ATFM delay. Our work provides an alternative tool for airports and airlines managers for estimating flight delays at the strategic phase

Numerical Analysis of the Mechanical Behavior and Failure Mode of Jointed Rock under Uniaxial Tensile Loading

In the field of rock engineering, tensile failure is one of the most significant failure modes due to the presence of joints/fractures. However, due to the limitations of current laboratory testing, it is difficult to carry out direct tensile tests on jointed rock specimens in the laboratory. To study the effect of joints on the mechanical behavior and failure mode of jointed rock specimens, a three-point modeling method that can consider arbitrarily arranged rock joints is deduced and applied to discrete element simulation. The effects of different joint angles (the inclination angle α, rotation angle β, and superimposed angle γ of α and β, where γ is the angle between the joint and horizontal plane), the density (n), and the rate of cutting area (RCA) of the specimen loading surface (LSS) on the tensile strength (σt), elastic modulus in tension (Et), and failure mode of the specimens were analyzed. The results show that the joint angle (considering α, β, and γ) and RCA have a significant effect on the resulting σt and failure mode, while n has a significant effect on Et. The failure mode of the specimen changes from tensile failure along the joint to direct tensile failure of the specimen as γ increases, and the mechanical behavior transitions from unstable to stable. In addition, the main influence of γ on the mechanical behavior of specimens is revealed, and the change process of the failure mode after the cutting of the LSS is analyzed. The present research can be utilized for multiple purposes, including the joint development of surrounding rock and failure dominated by tensile failure in underground engineering, especially for tunnels, roadways, chambers, and so forth

Evapotranspiration of Winter Wheat in the Semi-Arid Southeastern Loess Plateau Based on Multi-Source Satellite Data

Continuous monitoring of evapotranspiration (ET) at high spatio-temporal resolutions is vital for managing agricultural water resources in arid and semi-arid regions. This study used the enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM) to calculate the ET of winter wheat between the green-up and milk stages in Linfen Basin, a typical, semi-arid area of the Loess Plateau, at temporal and spatial resolutions of 30 m and 8 d, respectively. We then analyzed the impact of meteorological factors on ET and its variation during the main growth period of winter wheat. The fused ET data displayed the spatial details of the OLI ET data better and could accurately reflect ET variation and local sudden variations during the main growth period of winter wheat. Moreover, winter wheat ET in rain-fed areas is more heavily influenced by meteorological factors, and the effect is more direct. Affected by the synergistic effect of wind velocity, precipitation, and temperature, the ET of winter wheat in rain-fed area was lower in the green-up stage. Then, ET gradually increased, reaching its maximum in the heading–grain filling stage. At the jointing stage, temperature had a significant effect on ET. A combination of precipitation and temperature had the greatest impact on the ET of winter wheat in the heading–filling stage. In the milk stage, meteorological factors had a minor impact on ET. This study serves as a reference for ET in winter wheat in semi-arid areas and its influencing meteorological factors, which can assist in drought mitigation and regional food security strategies