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Tailings storage facilities (TSFs) are being built globally for containing the chief solid waste stream from mining industry. Catastrophic TSF breach accidents have occurred frequently since the beginning of the 21st century, causing severe impacts on the environment, economy and community safety. The recent example is the 2019 Brumadinho accident in Brazil that released 12 million m3 of tailings and killed more than 249 people. The foreknowledge of the TSF breach run out overland flow can be crucial to prevent or minimize possible losses. Using the Digital Surface Model (DSM) terrain data and the smoothed particle hydrodynamics (SPH) numerical method, this study proposed a procedure to predict the routings of hypothetical TSF breach run out flow over downstream complex terrain. A case study of a planning TSF site in Guizhou Province of China was carried out to evaluate its applicability. The results suggested that the maximum routing distance of the TSF breach run out flow was 1.45 km. At 240 s, the run out flow began to impact the downstream viaduct piers with the maximum submerged depth of 3.3 m and the maximum impact force of 21.8 kPa. Essential protective measures were recommended before the TSF site construction. The proposed procedure is then recommended for the safety management of the TSFs globally.

Tailings dams, as essential mining structures, are being built globally for containing the chief waste stream of the mining industry. Catastrophic tailings dam breaches have occurred frequently over the past decade, causing severe impacts on the environment, economy, and human health. The foreknowledge of the tailings dam breach overland flow is crucial for the risk assessment and emergency response planning in order to prevent or minimize possible losses. Using unmanned aerial vehicles (UAV) photogrammetry and smoothed particle hydrodynamics (SPH) numerical method, this study proposed a multidisciplinary procedure for modelling a hypothetical tailings dam breach run out flow over the downstream complex terrain. A case study on a 97-m-height tailings dam in Shandong Province of China was carried out. The proposed procedure was proven applicable to determine the overland tailings flow. The submerged area and flow velocities suggested that the downstream G2 highway would hardly be threatened and more concerns should be paid on the factory plants and workers deployed between the dam toe and the highway. Additionally, the application of UAV photogrammetry in the mining industry as a supplementary surveying method can be further expanded, especially for the numerous small-scale mining sites. The proposed procedure is then recommended for the safety management of the tailings&rsquo, storage facilities globally.

Monitoring vegetation change and their potential drivers are important to environmental management. Previous studies on vegetation change detection and driver discrimination were two independent fields. Specifically, change detection methods focus on nonlinear and linear change behaviors, i.e., abrupt change (AC) and gradual change (GC). But driver discrimination studies mainly used linear coupling models which rarely concerned the nonlinear behaviors of vegetation. The two diagnoses need be treated as sequential flow because they have inner causality mechanisms. Furthermore, ACs concealed in time series may induce over/under-estimate contributions from human. We chose the Yangtze River Basin of China (YRB) as a study area, first separated ACs from GCs using breaks for additive and seasonal trend method, then discriminated drivers of GCs using optimized Restrend method. Results showed that (1) 2.83% of YRB were ACs with hotspots in 1998 (30.2%), 2003 (10.4%), and 2002 (7.6%); 66.7% of YRB experienced GC with 94.8% of which were positive; and (2) climate induced more area but less dramatic GCs than human activities. Further analysis showed that temperature was the main climate driver to GCs, while human-induced GCs were related to local eco-policies. The widely occurring ACs in 1998 were related to the flooding catastrophe, while the dramatic ACs in sub-basin 12 in 2003 may result from urbanization. This paper provides clear insights on the vegetation changes and their drivers at a relatively long perspective (i.e., 34 years). Sequential combination of specifying different vegetation behaviors with driver analysis could improve driver characterizations, which is key to environmental assessment and management in YRB.

An assessment model for the satisfied degree of crop water requirements (CWR) on the grid scale, the CropWRA model, is developed to support precise management of agricultural water resources. On the grid scale, we urge that the CWR satisfied degree is not only rested with the abundance of water resources in a region, but also related to crop types, growing periods, water accessibility, etc. The CropWRA model also consists of corresponding indexes such as the CWR characteristics, crop planting combination and proportion, available water of agricultural production, water accessibility, etc. In this case study, the CWR satisfied degree of main food crops is evaluated with DEM data, hydrological data, meteorological and climate data, crop experiment and observation data, and statistical data in Hanjiang River Basin, China. In general, the results show that agricultural water resources can satisfy the CWR but the spatial differences are profoundly remarkable. The CropWRA index varies from -20% to 200%, and this difference is the comprehensive effects caused by the topography, river system, crop planting combination, land use, and water resources composition, etc. CropWRA model reveals the spatial differences in the relationships of CWR supply and demand and can provide the data support for precise water resource allocation.

Adaptability evaluation of reservoirs needs to be performed before natural gas flooding. However, the current evaluation methods consider the reservoir pressure and minimum miscible pressure (MMP) as separate parameters to evaluate the miscibility, which ignores the correlation between reservoir pressure and MMP. Also, the effect of reservoir pressure on injectivity is also neglected, while higher pressure than MMP may not improve the miscibility but increase the difficulty of gas injection. Furthermore, evaluation range of each index is inconsistent. Therefore, this paper proposes an improved evaluation system by introducing the miscible ability and optimizing the evaluation criteria to better evaluate the adaptability of natural gas flooding in enhancing oil recovery. The miscible ability is newly defined to evaluate the impact of reservoir pressure on miscibility, and multi-level evaluation model is further developed which includes 12 indexes based on reservoir/fluid/rock properties. The evaluation criteria are established by optimizing parameter intervals. The adaptability of BQ Oil field is assessed using Analytic Hierarchy Process (AHP) and fuzzy evaluation. Field application validates the reliability of the proposed evaluation system. It can be used to quickly evaluate the adaptability of natural gas flooding, which could improve success rate of natural gas flooding and reduce the costs.

Fifteen individual perfluoroalkyl substances (PFASs) were analyzed in 22 sediment samples collected from Anqing urban lakes (Anhui province, China) by ultra-performance liquid chromatography–tandem mass spectrometry (UPLC–MS/MS). Total PFAS concentration was between 0.61 and 26 ng g− 1 dry weight. Perfluorooctane sulfonate (PFOS) was the dominant PFAS contaminant, with a concentration range of

Traditional assessments of water resources use water availability as an evaluating metric. Water availability is a statistical average and cannot reflect the spatial differences of water resources in a region or basin. This assessment usually engenders a paradox, that is, water resources are abundant in a region but it is difficult to obtain water for the people on some spatial points in this region. In this study we define a new term, water accessibility, to eliminate this paradox and develop a model of water accessibility (the SHRD model) to meet the need of spatial details in water resources assessment at the grid scale. In the case study the water accessibility of the Hanjiang River Basin is mapped and assessed by the SHRD model. The comprehensive index of water accessibility is 0 to 4.5 and tends to increase from northwest to southeast in the study area. The results of the SHRD model can show the spatial pattern of water accessibility in a region, and can server a more finely-tuned water resources management approach. This model and method push the macroscopic (regional) water resources assessment forward from the microcosmic (raster cell) analysis.

Discriminating the significant human-induced vegetation changes over the past 15 years could help local governments review the effects of eco-programs and develop sustainable land use policies in arid/semi-arid ecosystems. We used the residual trends method (RESTREND) to estimate the human-induced and climate-induced vegetation changes. Two typical regions in the Horqin Sandy Land of China were selected as study areas. We first detected vegetation dynamics between 2000–2014 using Sen’s slope estimation and the Mann–Kendall test detection method (SMK) based on the Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) time series, then used RESTREND to profile human modifications in areas of significant vegetation change. RESTREND was optimized using statistical and trajectory analysis to automatically identify flexible spatially homogeneous neighborhoods, which were essential for determining the reference areas. The results indicated the following. (1) Obvious vegetation increases happened in both regions, but Naiman (64.1%) increased more than Ar Horqin (16.8%). (2) Climate and human drivers both contributed to significant changes. The two factors contributed equally to vegetation change in Ar Horqin, while human drivers contributed more in Naiman. (3) Human factors had a stronger influence on ecosystems, and were more responsible for vegetation decreases in both regions. Further evidences showed that the primary human drivers varied in regions. Grassland eco-management was the key driver in Ar Horqin, while farming was the key factor for vegetation change in Naiman.

Discriminating human-induced vegetation change is essential for sustainable managements of arid and semi-arid ecosystems. Residual Trends method (RESTREND), an effective quantitative method, has been widely used to discriminate human-induced vegetation changes in specific arid and semi-arid ecosystems. However, how to define homogeneous spatial neighborhood to determine reference pixel for estimating potential climate-solely-induced vegetation growth is still a challenge. This paper firstly detected vegetation dynamics in ArHorqin Banner of China from 2000 to 2014 by Mann-Kendall method, and then used RESTREND to profile human-induced changes. We optimized strategy in RESTREND by using statistical analysis and trajectory analysis to automatically define flexible homogeneous neighborhood. Results indicated that 18.6% of study area had significantly changes. Both climate change and human activities contributed to the changes. The influence of human activities on vegetation dynamics is more than climate change, and it was the main driver for vegetation decrease in study area.

A year-long field study on the seasonal characteristics of fine particulate matter (PM 2.5 ) was conducted at the Qilian Shan Station of Glaciology and Ecologic Environment (QSS), a remote site on the northeast edge of the Tibetan Plateau. The PM 2.5 samples were collected weekly using a low volume (16.7 L/min) sampler, and then analyzed by ion chromatography for the water soluble ionic species (WSIs). The annual average mass loading of PM 2.5 , retrieved from co-located measurement on aerosol size distribution, was 9.5 ± 5.4 μg m − 3 with WSIs accounting for 39 ± 2%. The WSIs were dominated by SO 4 2 − (39%), CO 3 2 − (19%), Ca 2 + (16%), NO 3 − (10%), and NH 4 + (6%), suggesting important contributions from both anthropogenic aerosol and mineral dust. The mass loading of total WSIs showed a seasonal variation with higher concentrations in spring (6.3 μg m − 3 ) and summer (5.1 μg m − 3 ) and lower concentrations in winter (2.2 μg m − 3 ) and fall (1.7 μg m − 3 ). A linear regression of ammonium versus sulfate by equivalent concentration showed a slope of 0.51, suggesting an excess of acids. The excess sulfuric and nitric acids likely reacted with mineral dust, as evidenced by the tight correlation between [Ca 2 + + NH 4 + ] and [SO 4 2 − + NO 3 − ]. The oxidation ratios of nitrogen and sulfur estimated based on the datasets of SO 2 and NO 2 from the closest air quality station at Jiayuguan (~ 150 km from sampling site) showed that the gas-particle partitioning of nitrogen on dust was more efficient than that of sulfur. The size distribution of SO 4 2 − showed a dominant accumulation mode, with a mode diameter ( D p ) ranging from 0.18 to 0.56 μm. In comparison, NO 3 − and Ca 2 + showed a prominent coarse mode with D p ranging from 1 to 10 μm. The results of air mass trajectory cluster and potential source contribution function analysis demonstrated that the source regions of the mineral dust were located in the arid areas of northwest China while the anthropogenic aerosol was likely from urban areas in the low elevation areas to the east of QSS. The effects of meteorological parameters on the particle mass loading were also evaluated.

Land consolidation changes the land use types and then the biomass. The measure and calculation of biomass fore-and-aft land consolidation worked out by the sample plot method in terms of arbor, shrub, herbage plants and crop. The result shows that the biomass is increased 580 t after land consolidation, meaning the impression of land consolidation is remarkable in general. The results of monomial analysis are as follows: (1) the biomass of sparse forest is no changed fore-and aft land consolidation, but its ratio of biomass is reduced down 2.5% and its ecological influence is slightly weakened; (2) the biomass sum of manpower forest and sparse forest is increased up 6% after land consolidation, so that the total ecological influence of woodland is enhanced; (3) the waste grassplot is disappear of land consolidation, so that its ecological influence; (4) the total biomass of dry-land crop is all most no change, but its influence is reduced down 17.87%; (5) the total biomass of rice is increased up 477.94 t after land consolidation, account of 82.4% of increased amount and its total ecological influence is up to 14.12%. The results also show: (1) the structure and function of regional ecosystem will be changed by land consolidation and the biomass will be changed accordingly; (2) marked ecological influence will be induced from the biomass change, not only the natural ecosystem, but also the human ecosystem.

Tailings pond plays a very important role in the construction of mine engineering. At the same time, tailings pond also produces huge pollution to the environment. If dam break occurs, it will cause loss of people and property. In this paper, a tailings pond management system based on RSCIC is studied, the monitoring content of the system is determined, the more innovative system and hardware are emphasized, the program flow chart of digital processing is put forward. Adopting scientific and effective means to manage the tailing dam automatically can not only strengthen the safety protection of the tailing dam, but also provide a certain theoretical basis for the construction of other digital tailings dam projects.

The concentration and size distribution of aerosol particles in the range of 0.25-32 mu m was monitored with an optical particle counter from 2009 to 2011 at the Qilian Shan Station of Glaciology and Ecologic Environment (QSS) (39.50N, 96.51E

Water resources are one of the important factors that influence regional crop production and the food security of humans. Most traditional models of crop water demand analysis are built on the basis of a certain crop or macroscopic analysis, which neglect regional crop allocation and the difference of water demand in different crop growing periods. In this paper, a new assessing model, the satisfied degree of crop water requirement, is developed to assess the impacts of water resources on production of six main food crops in China. The six main food crops are spring wheat, winter wheat, corn, early season rice, middle-season rice and late rice. The results show that: (1) there are serious risks of water shortage in China, even in south China with its abundant precipitation; (2) the satisfied degree of crop water demand represents great temporal-spatial changes. On spatial distribution the risks are high in major bases of food production due to influences of cropping system and crop-combinations. Northwest China is a special interesting case. In seasonal fluctuation water shortage is severe in March and September. These risks seriously restrict food production in China. The results also show that the strategic measures of water resources management must be chosen carefully to deal with food security and regional sustainable development in China.