The behavior and fates of environmental pollutants within the cryosphere and the associated environmental impacts are of increasing concerns in the context of global warming. The Tibetan Plateau (TP), also known as the "Third Pole", represents one of the most important cryospheric regions in the world. Mercury (Hg) is recognized as a global pollutant. Here, we summarize the current knowledge of Hg concentration levels, pools and spatio-temporal distribution in cryospheric environments (e.g., glacier, permafrost), and its transfer and potential cycle in the TP cryospheric region. Transboundary transport of anthropogenic Hg from the surrounding heavily-polluted regions, such as South and Southeast Asia, provides significant sources of atmospheric Hg depositions onto the TP cryosphere. We concluded that the melting of the cryosphere on the TP represents an increasing source of Hg and brings a risk to the TP environment. In addition, global warming acts as an important catalyst accelerating the release of legacy Hg from the melting cryosphere, adversely impacting ecosystems and biological health. Furthermore, we emphasize on the remaining gaps and proposed issues needed to be addressed in future work, including enhancing our knowledge on some key release pathways and the related environmental effects of Hg in the cryospheric region, integrated observation and consideration of Hg distribution, migration and cycle processes at a key region, and uses of Hg isotopic technical and Hg models to improve the understanding of Hg cycling in the TP cryospheric region.

This study presents a numerical method based on the surface temperature data and the ground temperature increase in Daqing for predicting temperature field distribution in the Binzhou Railway subgrade and analyzing the temporal and spatial distribution of freeze-thaw status of railway subgrade. The calibrated numerical method is applied to simulate the temperature field distribution and roadbed vibrational response of the railway subgrade with a thermal insulation layer at different seasons. The results show the following: (1) The thermal insulation layer can remarkably increase the soil temperature below it and maximum frost depth in the subgrade. (2) Thermal insulation can effectively reduce the subgrade vibration and protect it from frost damage. (3) Given that the strength requirements are met, the insulation layer should be buried as shallow as possible to effectively reduce the subgrade vibration response. The research findings provide theoretical support for the frost damage prevention of railway subgrades in seasonally frozen regions.

Potential of the Random Forest Model on mapping of different desertification processes was studied in Muttuma watershed of mid-Murrumbidgee river region of New South Wales, Australia. Desertification vulnerability index was developed using climate, terrain, vegetation, soil and land quality indices to identify environmentally sensitive areas for desertification. Random Forest Model (RFM) was used to predict the different desertification processes such as soil erosion, salinization and waterlogging in the watershed and the information needed to train classification algorithms was obtained from satellite imagery interpretation and ground truth data. Climatic factors (evaporation, rainfall, temperature), terrain factors (aspect, slope, slope length, steepness, and wetness index), soil properties (pH, organic carbon, clay and sand content) and vulnerability indices were used as an explanatory variable. Classification accuracy and kappa index were calculated for training and testing datasets. We recorded an overall accuracy rate of 87.7% and 72.1% for training and testing sites, respectively. We found larger discrepancies between overall accuracy rate and kappa index for testing datasets (72.2% and 27.5%, respectively) suggesting that all the classes are not predicted well. The prediction of soil erosion and no desertification process was good and poor for salinization and water-logging process. Overall, the results observed give a new idea of using the knowledge of desertification process in training areas that can be used to predict the desertification processes at unvisited areas.

Samples from the Horqin sandy land were exposed to a series of wind velocities, and sink particles were collected at the end of the diffusion section of a wind tunnel. Grain sizes of collected samples show great variation because of the granularity difference of the surface samples. The original samples show lower average content of SiO₂ and higher average content of Al₂O₃, Fe₂O₃, MgO, CaO, Na₂O, and K₂O than collected samples. Compared with other dust source areas in China, the Horqin sandy land had higher content of Zr, Ba, SiO₂, Al₂O₃ and K₂O. Compared with the average upper continental crust (UCC) composition, surface samples were rich in the content of Y, Zr, Nb, Ba, La, Nd. Geochemistry characteristics of fine grain components of the Horqin sandy land differ from those from other dust source regions, because fine-grained particles in the Horqin sandy land were mostly derived from various local deposits formed in its unique depositional environments influenced by several tectonic activities.

Patterns in species geographic range size are relatively well-known for vertebrates, but still poorly known for plants. Contrasts of these patterns between groups have rarely been investigated. With a detailed flora and fauna distribution database of Xinjiang, China, we used regression methods, redundancy analysis and random forests to explore the relationship of environment and body size with the geographic range size of plants, mammals and birds in Xinjiang and contrast these patterns between plants and animals. We found positive correlations between species range size and body size. The range size of plants was more influenced by water variables, while that of mammals and birds was largely influenced by temperature variables. The productivity variable, i.e., Enhanced Vegetation Index (EVI) was far more correlated with range size than climatic variables for both plants and animals, suggesting that vegetation productivity inferred from remote sensing data may be a good predictor of species range size for both plants and animals.

Solar energy is clean and renewable energy that plays an important role in mitigating impacts of environmental problems and climate change. Solar radiation received on the earth's surface determines the efficiency of power generation and the location and layout of photovoltaic arrays. In this paper, the average daily solar radiation of 77 stations in China from 1957 to 2016 was analyzed in terms of spatial and temporal characteristics. The results indicate that Xinjiang, the Qinghai-Tibet Plateau, North, Central and East China show a decreasing trend with an average of 2.54×10^-3 MJ/(m²?10a), while Northwest and Northeast China are basically stabilized, and Southwest China shows a clear increasing trend with an average increase of 1.79×10^-3 MJ/(m²?10a). The average daily solar radiation in summer and winter in China from 1957 to 2016 was 18.74 MJ/m² and 9.09 MJ/m², respectively. Except for spring in Northwest, East and South China, and summer in northeast China, the average daily solar radiation in all other regions show a downward trend. A critical point for the change is 1983 in the average daily solar radiation. Meanwhile, large-scale (25-30 years) oscillation changes are more obvious, while small-scale (5-10 years) changes are stable and have a global scope. The average daily solar radiation shows an increasing-decreasing gradient from west to east, which can be divided into three areas west of 80°E, 80°E-100°E and east of 100°E. The average daily solar radiation was 2.07 MJ/m² in the 1980s, and that in 1990s lower than that in the 1960s and the 1970s. The average daily solar radiation has rebounded in the 21st century, but overall it is still lower than the average daily solar radiation from 1957 to 2016 (13.87 MJ/m²).