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Abstract Atmospheric dustfall is solid air pollutant, has a major impact on the environment and human health. The objective of this study was to investigate the microscopic characteristics and sources of atmospheric dustfall in open-pit mining coal resource-based city in the arid desert area of Northwest China. The characteristics of size and shape factors, variation of shape factors with size distribution, types of individual particles, and sources of atmospheric dustfall, which were collected in the open-pit mining area and surrounding areas, were analyzed by X-ray diffraction (XRD) and scanning electron microscopy coupled with an energy dispersive spectrometer (SEM–EDS) combined with graphical method and shape factors. The results showed that the atmospheric dustfall in all functional areas was dominated by coarse-grained particles. The shape of the atmospheric dustfall deviated from spherical shape, and with decreasing particle size, the difference in shape factors increased in each functional area. The EDS and XRD analyses indicated the presence of 13 types of particles. The sources were mainly local and included soil dust from each functional area; industrial dust, construction dust, biogenic impurities, fossil fuel combustion, wear products of motor vehicle parts, motor vehicle exhaust emissions, and emission and excreta from biological activities in each functional area except the desert area; emissions from a steel plant in the industrial area; coal-associated ore, coal dust, coal gangue emissions, and emissions from the spontaneous combustion of coal gangue in the open-pit mining area; secondary chemical crystallization products in the industrial area and the open-pit mining area; dust generated by vehicles abrading the surface of the off-mine coal road and in the open-pit mining area.

The southern red soil region (SRSR) of China, a region that is environmentally sensitive, suffers severe soil erosion (SE) as a result of climate change and human activity. The factors driving SE changes in the SRSR of China under changing settings have, however, only been the subject of a small number of research. Changting County is a typical SE area in the SRSR of China. The spatiotemporal variation characteristics of SE in Changting County from 2000 to 2020 were investigated using the revised universal soil loss equation (RUSLE), while the dominant factors influencing the spatiotemporal dynamic change of SE were analyzed using the optimal parametric geographical detector (OPGD) and logarithmic mean Divisia Index (LMDI). The results showed that the average annual soil erosion modulus in Changting County shows a decreasing trend, with the SE modulus decreased from 10.00 t·hm−2·a−1 in 2000 to 3.38 t·hm−2·a−1 in 2020. Slight SE intensity was the dominant SE class, accounting for more than 75% of the total area, and the proportion is trending upwards. Natural and anthropogenic factors showed significant effects on the spatial variation of SE, of which land use and vegetation cover were the main factors influencing the spatial distribution of SE. Furthermore, the interaction between these two dominant factors explained greatly the spatial variation of SE. The mitigation of SE was mainly attributed to the increase in vegetation cover following the implementation of various ecological projects, contributing to the reduction of SE by 68.7%. In addition, the changes in land use types and rainfall amounts also played positive roles in reducing SE, showing contributions of 20.2% and 11.1%, respectively.

The Steam Generator (SG) is a crucial component of a Nuclear Power Plant (NPP), generating steam to transfer heat from the primary loop to the secondary loop. The control performance of the Steam Generator Level Control System (SGLCS) plays a crucial role in the normal operation of the SG. To improve the system’s performance, the parameters of the control system should be optimized. However, the steam generator and its corresponding control system are highly complex, exhibiting nonlinearity and time-varying properties. Conventional parameter-setting methods mainly rely on engineers’ experience, and are laborious and time-intensive. To tackle the aforementioned challenges, a Model-Free Optimization (MFO) method based on Knowledge-informed Historical Gradient-based Simultaneous Perturbation Stochastic Approximation (GK-SPSA) is applied to the performance optimization of the steam generator level control system. The GK-SPSA algorithm is a variant of the traditional SPSA algorithm. The fundamental idea of this revised algorithm is to maximize the utilization of historical gradient information generated during the optimization process of the SPSA algorithm, with the aim of enhancing overall algorithm performance in a model-free optimization context. Based on the effective utilization of historical gradient information, the GK-SPSA algorithm exhibits two improvements over the SPSA algorithm. The first improvement is related to the recognition of the online optimization progress, utilizing the state of the optimization progress to dynamically adjust the optimization step size. The second improvement is related to gradient estimation compensation, employing compensation rules to enhance the accuracy of gradient estimation, thus improving the optimization efficiency. Through simulation experiments, it can be observed that there is not much difference in the final iteration values among the GK-SPSA, IK-SPSA, and SPSA methods. However, the iteration count of GK-SPSA is reduced by about 20% compared to SPSA and by 11.11% compared to Knowledge-informed SPSA (IK-SPSA). The results indicate that this method can significantly improve the efficiency of parameter tuning for the liquid level control system of a steam generator.

The steam generator is an important piece of energy exchange equipment for nuclear power plants, and the level control of the steam generator plays a key role in the stable operation of the plants. To improve the level control performance of the steam generator, it is necessary to adjust the parameters of the level control system during the commissioning process of nuclear power plants. However, the parameter setting process relies heavily on the experience of engineers, requires a lot of historical data, and is difficult to ensure the best. To address these issues, this paper proposes a hybrid iterative model reconstruction-based steam generator level control performance optimization method based on the idea of data-driven optimization. The method proposes a fusion idea and implementation mechanism in which process data and the hybrid model are jointly driven under the data-driven framework to maximize the advantages of different modeling mechanisms to achieve the performance optimization of a steam generator level control system. The method first constructs the initial dataset with a small-sample Latin-square experiment design and then builds two different fitting models, SVM and Kriging, based on the initial dataset respectively, under the hybrid model fusion idea. After that, the particle swarm optimization algorithm is used to calculate the optimal point of the current valid model, and the optimization process is controlled by establishing the iteration termination judgment based on the historical iteration data. Then, the current iteration point is used to dynamically reconstruct the two types of models. Finally, the two types of models are dynamically reconstructed using the current iteration points. The above process is iterated until the optimal iterative process of the system is satisfied. From the experimental results, it can be seen that compared with two types of single-model optimization methods, this method can reduce the iteration final value by 13.57% and 16.27%, respectively, with a slightly increased number of iterations. These results indicate that this method can significantly improve the efficiency of optimizing the control performance of the steam generator liquid level.

Canopy interception is an important part of forest ecosystem hydrological processes. It is the first stage of water distribution when rainfall reaches the canopy and has an important impact on nutrient inputs and water exchange. Pinus tabulaeformis is a main tree species in the rocky mountain areas of Northern China, and it is also a primary species for artificial afforestation. In previous studies of canopy interception, applications of the revised Gash model did not take rainfall characteristics into account. Therefore, in this study, rainfall patterns were divided according to the local rainfall characteristics in the rocky mountainous areas of Northern China. Rainfall was divided into three patterns. Rain pattern A was the main rainfall type. Rainfall patterns B and C were two types of rainstorms. Next, the revised Gash model was used to simulate Pinus tabulaeformis plantations under different rainfall patterns. The results showed that the canopy interception rate of Pinus tabulaeformis plantations in this area ranged from 14.7% to 17.9%. The revised Gash model can be used to simulate Pinus tabulaeformis plantations in the rocky mountainous areas of Northern China, with good simulation results for more than 80% of the conventional rainfall patterns. Furthermore, the canopy interception effect of simulated cumulative rainfall events was better than the individual rainfall event. The simulation effect for special rainfall patterns was not good, so it is necessary to improve the model parameters or collect more rainfall samples. These results can be used to explore the applicability of the revised Gash model in Pinus tabulaeformis plantations in the rocky mountain areas of Northern China. They also demonstrate different applicability of the model under different rainfall characteristics.

The steam generator (SG) is a critical component of the steam supply system in the nuclear power plant (NPP). Hence, it is necessary to control the SG level well to ensure the stable operation of the NPPs. However, its dynamic level response process has significant nonlinearity (such as the ‘swell and shrinks’ effect) and time-varying properties. As most of the SG level control systems (SGLCS) are constructed based on the Proportional-Integral-Derivative (PID) controllers with fixed parameters, the controller parameters should be optimized to improve the performance of the SGLCS. However, traditional parameters tuning methods are generally experience-based, cumbersome, and time-consuming, and it is difficult to obtain the optimal parameters. To address the challenge, this study adopts a knowledge-informed simultaneous perturbation stochastic approximation (IK-SPSA) based on adjacent iteration points information to improve the performance of the SGLCS. Rather than the traditional controller parameter tuning method, the IK-SPSA method optimizes the control system directly by using measurements of control performance. The method’s efficiency lies in the following aspects. Firstly, with the help of historical information during the optimization process, the IK-SPSA can dynamically sense the current status of the optimization process. Secondly, it can accomplish the iteration step size tuning adaptively according to the optimization process’s current status, reducing the optimization cost. Thirdly, it has the stochastic characteristic of simultaneous perturbation, which gives it high optimization efficiency to optimize high dimensional controller parameters. Fourthly, it incorporates an intelligent termination control mechanism to accomplish optimization progress control. This mechanism could terminate the optimization process intelligently through historical iterative process information, avoiding unnecessary iterations. The optimization method can improve the stability, safety, and economy of SGLCS. The simulation results demonstrated the effectiveness and efficiency of the method.

During ecological restoration, it is necessary to comprehensively consider the state of vegetation in climate–soil–vegetation systems. The theory of ecohydrological optimality assumes that this state tends to reach long-term dynamic equilibrium between the available water supply of the system and the water demand of vegetation, which is driven by the maximization of productivity. This study aimed to understand the factors that affect the spatial distribution of vegetation and simulate the ideal vegetation coverage (M0) that a specific climate and soil can maintain under an equilibrium state. The ecohydrological optimality model was applied based on meteorological, soil, and vegetation data during the 2000–2018 growing seasons, and the sensitivity of the simulated results to input data under distinct vegetation and soil conditions was also considered in the Yongding River watershed, China. The results revealed that the average observed vegetation coverage (M) was affected by precipitation characteristic factors, followed by wind speed and relative humidity. The M, as a whole, exhibited horizontal zonal changes from a spatial perspective, with an average value of 0.502, whereas the average M0 was 0.475. The ecohydrological optimality theory ignores the drought resistance measures evolved by vegetation in high vegetation coverage areas and is applicable to simulate the long-term average vegetation coverage that minimizes water stress and maximizes productivity. The differences between M and M0 increased from the northwest to the southeast of this area, with a maximum value exceeding 0.3. Meteorological factors were the most sensitive factors of this model, and the M0 of the steppe was most sensitive to the stem fraction, mean storm depth, and air temperature. Whether soil factors are sensitive depends on soil texture. Overall, the study of the carrying capacity of vegetation in the natural environment contributes to providing new insights into vegetation restoration and the conservation of water resources.

The hazards from wind, sand, and soil erosion caused by human activities, such as residue slopes in abandoned urban mines, have resulted in a vicious circle of environmental degradation. Selecting the optimal protective engineering method in mountainous areas has become a major difficulty in recent years, and the primary goal of our research is to accelerate the process of ecosystem reconstruction to maintain water and soil quality. In this study, cover soil of 10, 20, and 30 cm in depth was spread on the 30° accumulation slopes composed of loose residue from the Huangyuan Quarry, Beijing, and combined with two protection measures: eco-bags and bamboo fences. Runoff and soil loss from the aboveground, soil and residue layers were measured under rainfall intensities of 30, 60 and 120 mm/h generated with a rainfall simulator. The results indicated that both eco-bags and bamboo fences decreased runoff and soil loss. Bamboo fences were better at intercepting water under low runoff, whereas soil loss was more strongly reduced by eco-bags. The analysis also demonstrated that the depth of soil cover had an effect on runoff and soil loss. These findings will enrich the understanding of the effects of human activities on surface mines and provide a scientific basis for the ecological restoration of mines using engineering methods.

With the increasing proportion of open-pit coal mining in the coal mining industry in China, a series of potential safety hazards, environmental pollution, ecological damage and other problems caused by open-pit coal mining have attracted a great deal of attention. Scientifically determining the appropriate mining right scope of an open-pit coal mine can prevent various problems caused by coal mining from the source. In this study, according to the characteristics of open-pit coal mining and the environmental characteristics in arid areas, 15 indicators were selected and their weights were determined from the three perspectives of geological environment, social environment and ecological environment by using the AHP. Based on the spatial analysis function of ArcGIS, a digital evaluation model was established for the corresponding influencing factors, and a comprehensive evaluation model for setting the mining right range was constructed by superimposing the weights. Finally, four mining areas were identified within the study area in Wuhai, Inner Mongolia, and their ecological values were calculated to determine the mining area with the lowest ecological impact. [ABSTRACT FROM AUTHOR]

Soil wind erosion is an important factor that inhibits social activities and economic development in the arid desert region of northwestern China. In order to reveal the distribution of soil wind erosion climate erosivity in the arid desert region of northwestern China, the spatial and temporal variation and transfer characteristics of wind erosion climate erosivity in the region were evaluated by referring to China's regional ground long-time series meteorological element driving data, and applying the ArcGIS software analysis. The study results show that: (1) Against a backdrop that such meteorological factors as precipitation amount, wind speed, and average temperature over multiple years all increase progressively decade by decade, the wind erosion climate erosivity in the northwest arid desert region is decreasing as a whole. The C values of most areas are within the range of 0 to 100. However, the climate erosivity in the hinterland and a few areas is increasing, with C values higher than 150. (2) The monthly variation of the C value varies significantly. The greatest variation occurs in spring and summer, followed by the variation in winter, while the slightest variation occurs in autumn. Through the abrupt change test, it is found that the wind erosion climate erosivity in spring has the strongest variation, with four abrupt change points and a pattern of long-term fluctuating decline. (3) The soil wind erosion in the region gradually decreases from the hinterland to the peripheral areas, with the areas highly affected by erosion increasing yearly. (4) The spatial-temporal transfer and variation of wind erosion climate erosivity present an overall pattern of slight decrease. However, in some areas, they increase or show an apparent trend of increase. The study results have provided relevant theoretical evidence and scientific support for preventing and controlling wind–sand disasters in the arid desert region of northwestern China. [ABSTRACT FROM AUTHOR]

In order to clarify the ecological restoration direction, this study investigated the limiting factors of the ecological restoration of the dump of Rujigou Open-pit Coal Mine in the Helan Mountain Nature Reserve from the aspects of climate, topography, and soil physicochemical properties. The main results are as follows: (1) In terms of climate, the main limiting factors in the study area were low precipitation (<200 mm) with uneven annual distribution, high evaporation (2000 mm), low temperature, less effective accumulated temperature, and large number of gale days (≥150 days). (2) The topographic limiting factors were steep slope (30°–36°) and long slope length (10–44 m). (3) In terms of soil, the main limiting factors were high contents of sand (73.40%±2.18%) and clay (13.21%±1.37%), low porosity (30.89%±0.83%), and low contents of total nitrogen (0.67±0.05 g kg–1), hydrolytic nitrogen (14.23±0.48 mg kg–1) and available phosphorus (2.81±0.44 mg kg–1). The limiting factors of the ecological restoration of the study area mainly included drought and water shortage, less effective accumulated temperature, large number of days of strong wind, steep slope, long slope length, and soil depletion. In view of the above limiting factors, countermeasures such as slope foot support, slope level arrest and consolidation, slope cover, plant measures, and muck improvement can be considered. This study provides a scientific basis and theoretical support for the selection of appropriate ecological restoration measures and improvement of restoration effectiveness for open-pit mine dumps in arid areas such as the Helan Mountains. [ABSTRACT FROM AUTHOR]

While promoting economic and social development of China, open-pit coal mining will also cause irreversible harm to the surrounding environment due to disturbing the topsoil. Therefore, ecological restoration measures are urgently required. Vegetation cover is an important part of mine ecological restoration work. Suitable soil structure and nutrient conditions are the basis of normal plant growth and development. In this study, the slag, sand, humic acid, diammonium phosphate (DAP) and urea were selected as the improved materials to adjust the structure and fertility of the slag and improve the slag into a suitable vegetative substrate for plant growth. From among various configurations of the vegetative substrate, the most suitable substrate for plant growth was filtered by comparing the physical and chemical properties and their effects on Alfalfa growth under different treatments. The results showed that the application of fertilizers could increase the nutrient content of the vegetative substrate and increase the pH, but the growth of Alfalfa was not optimal under the high fertilization treatment. The addition of sand could mitigate the structural problems of slag, and sand also showed a certain degree of regulation on fertility. Moreover, the addition of appropriate amounts of humic acid can enhance slag maturation and stabilize the chemical properties of the vegetative substrate. According to the results, the most optimal slag-sand-humic acid ratio for the vegetative substrate of the dump site of the Dafeng Open-pit Coal Mine is 18:1:1. The findings are expected to offer a reference for the improvement method of slag in this area, which alleviates the shortage of soil resources. It provides support for ecological environmental protection in soil source area, and also offers a new idea for the resource utilization of slag in the ecological restoration. [ABSTRACT FROM AUTHOR]

In order to study the counterpoint configuration about the types of mining sites and ecological restoration technologies, open-pit coal mine dumps that had been ecologically restored, since many years, in the grassland mining area in western Inner Mongolia, were selected. A comprehensive evaluation of slope protection effect, vegetation restoration effect, soil improvement effect and engineering technology cost was carried out in order to classify the types of sites for open-pit coal mine dumps and to determine their counterpoint ecological restoration technology, so as to provide theoretical guidance and technical support for ecological restoration of the grassland mining area in western Inner Mongolia. The research results are as follows: (1) Soil thickness, slope gradient and slope aspect are the dominant factors affecting the site conditions of the dump site. Base on this, the dump site of the open-pit coal mine in the grassland mining area of western Inner Mongolia was divided into 9 types of sites. (2) For half-shade and half-sunny to thick soil gentle slope, we primarily recommend plant grid slope protection + planting + sowing + sprinkler irrigation, and the second recommendation is hexagonal brick slope protection + mortar masonry ditch + sowing + sprinkler irrigation; for half-shade and half-sunny to medium-thick soil gentle slope, we primarily recommend masonry skeleton slope protection + mortar masonry ditch + sowing + sprinkler irrigation, and the second recommendation is sowing + vegetation blanket coverage + sprinkler irrigation; for half-shade and half-sunny to thin soil gentle slope, it is recommended to use gravel capping + mortar masonry ditch. For sunny thick soil gentle slope, we primarily recommend eco bag blocking + planting + sowing + vegetation blanket coverage + sprinkler irrigation, and the second recommendation is eco bag blocking + sowing + grass curtain coverage grass curtain coverage + sprinkler irrigation; for sunny thick soil steep slope, it is recommended to use plant grid slope protection + mortar masonry retaining wall + sowing + sprinkler irrigation. For shade thick soil gentle slope, we primarily recommend eco bag blocking + planting + sowing + vegetation blanket coverage + sprinkler irrigation is preferred, and the second recommendation is planting bag stacking + mortar masonry retaining wall + sprinkler irrigation; for shade medium-thick soil gentle slope, it is recommended to use eco bag blocking + corrugated pipe drainage + sowing + vegetation blanket coverage + sprinkler irrigation; for the shade medium-thick soil steep slope, we primarily recommend eco bag blocking +sowing + grass curtain coverage + sprinkler irrigation, and the second recommendation is eco bag blocking + corrugated pipe drainage + sowing + vegetation blanket coverage + sprinkler irrigation. For thick soil platform, use of planting + sowing + sprinkler irrigation is recommended. The research results provide a scientific basis for selection of ecological restoration technologies in the grassland coal mining area in western Inner Mongolia. At the same time, with respect to the semi-arid grassland mining area with relatively fragile habitats, this research be of great significance to improve the greening benefits of the mining area and for improving the mining area and surrounding ecological environment. [ABSTRACT FROM AUTHOR]

As with other jurisdictions, China has introduced a range of newer technologies into its justice sector to promote greater access to justice, improve judicial transparency and to promote just outcomes for disputing parties with legal issues. Chinese courts' practice of embracing technology is unique as an overarching approach has been adopted by the central government to build the 'smart court' system across the entirety of its courts. Arguably, the smart court system, which relies on computer technologies that enable big data use, blockchain formation and advisory and determinative forms of artificial legal intelligence, has, to a certain degree, promoted easier access to justice, enabled faster dispute resolution, saved costs by moving judicial process online and ensured that judgments can be enforced. On the other hand, however, there are concerns relating to the use of some technologies that include the use of automated judgments, digital divide issues, judicial independence, as well as issues linked to privacy and data protection. This article concludes that some caution should be exercised in developing the 'smart court' system, primarily in relation to the oversight and introduction of more disruptive technologies to ensure that cheap and quick dispute resolution can be achieved without detrimental impacts on justice. [ABSTRACT FROM AUTHOR]

Background: Bovine papilloma is a neoplastic disease caused by bovine papillomaviruses (BPVs), which were recently divided into 5 genera and at least 24 genotypes. Objectives: The complete genome sequence of BPV type 15 (BPV Aks-02), a novel putative BPV type from skin samples from infected cows in Southern Xinjiang China, was determined by collecting warty lesions, followed by DNA extraction and amplicon sequencing. Methods: DNA was analyzed initially by polymerase chain reaction (PCR) using the degenerate primers FAP59 and FAP64. The complete genome sequences of the BPV Aks-02 were amplified by PCR using the amplification primers and sequencing primers. Sequence analysis and phylogenetic analysis were performed using bio-informatic software. Results: The nucleotide sequence of the L1 open reading frame (ORF) of BPV Aks-02 was 75% identity to the L1 ORF of BPV-9 reference strain from GenBank. The complete genome consisted of 7,189 base pairs (G + C content of 42.50%) that encoded 5 early (E8, E7, E1, E2, and E4) and 2 late (L1 and L2) genes. The E7 protein contained a consensus CX2CX29CX2C zinc-binding domain and a LxCxE motif. Among the different members of this group, the percentages of the complete genome and ORFs (including 5 early and 2 late ORFs) sequence identity of BPV Aks-02 were closer to the genus Xipapillomavirus 1 of the Xipapillomavirus genus. Phylogenetic analysis and sequence similarities based on the L1 ORF of BPV Aks-02 revealed the same cluster. Conclusions: The results suggest that BPV type (BPV Aks-02) clustered with members of the Xipapillomavirus genus as BPV 15 and were closely related to Xipapillomavirus 1. [ABSTRACT FROM AUTHOR]

Whole blood samples (472) were collected during the period of 2006-2008 from 15 cattle farms in seven districts of the Xinjiang Uygur Autonomous Region, which is a major pastoral area and represents 1/6 of Chinese territory. Bovine viral diarrhea virus (BVDV) was detected by nested reverse transcription polymerase chain reaction assay (RT-nPCR) and sequenced within the 5′-untranslated region of the genome. Approximately 43% (202 samples) were BVDV-positive. Of the positive samples, 24 were chosen for further sequencing, sequence comparisons, and phylogenetic reconstructions. The phylogenetic reconstructions demonstrated that these isolates clustered into either BVDV1b (18 samples) or BVDV1c (six samples) subgenotypes. None of the isolates sequenced showed any cytopathic effect in culture. Unlike previously published studies in Chinese cattle, no BVDV2 genotypes were detected. These results indicate that the predominant subgenotypes in Xinjiang are BVDV1b and BVDV1c. This finding can be useful for further BVDV epidemiological study in China. [ABSTRACT FROM AUTHOR]

This study attempts to analyze how precipitation and vegetation affect water yield in Haihe watershed. Based on the annual runoff and meteorological data, the water balance equation and the calibrated Zhang model were used to simulate the effects of precipitation and vegetation on water yield. The simulated results showed that the effect of precipitation on water yield was linear in mountainous area of Haihe watershed, and a 1 mm change (increase or decrease) in precipitation will cause a 0.51 mm change in water yield; under the mean annual precipitation of 534 mm, the effects of decreasing water yield by per unit cover ratio for forest, grassland, and farmland were 1.26, 0.47, and 0.69 mm, respectively. The decreased water yields for forest, grassland, and farmland were associated with aridity indexes by negative power functions, and indicate that the effect of vegetation on water yield was smaller in drier areas. For three vegetation types the effects of vegetation on water yield were similar for crops and grass, and were much larger for forest. [ABSTRACT FROM AUTHOR]