China experiences severe particulate matter (PM) pollution. Although a monitoring network for PM2.5 (diameter < 2.5 mu m) has been set up in more than 100 major Chinese cities, insufficient spatial coverage of observations limits the study of the temporal and spatial characteristics, influencing factors, and component of PM2.5. In this study, we conducted a one year air quality simulation using a regional climate-chemistry model and evaluated the simulation's performance based on in situ observations concerning meteorological elements and PM2.5 concentrations. The simulated results showed that, higher PM2.5 concentrations appeared in northern China and the Sichuan Basin, and the maximal value occurred in winter. Furthermore, Vertical PM2.5 concentrations presented a gradual decreasing trend from the surface, whereas in southern coastal cities the profiles were unsteady with a secondary peak in the lower layer. Meteorological conditions were conducive to both pollutant diffusion and removal in summer, whereas stagnant conditions appeared in winter, characterized by high sea level pressure (SLP), the lowest planetary boundary layer height (PBLH), and 2-m temperature (T2). In provincial capital cities, PM2.5 was positively correlated with residential emissions but negatively correlated with precipitation, 10-m wind speed, T2, PBLH, and industrial emissions. Finally, we utilized the simulation results to investigate the component variations of PM2.5. Results indicated that primary PM2.5 components had significantly higher concentrations in northern China where residential heating is the major source of PM2.5 emissions, whereas they had lower concentrations in southern China. Secondary components played a crucial role in PM2.5 mass in eastern China. This study provided a clear perspective of seasonal variations, horizontal and vertical distributions of PM2.5 and its components and influence factors, which could be used in subsequent studies to investigate the formation mechanism and emission sources of PM2.5.

The Qilian Mountains (QMs), located in the northeast part of the Qinghai-Tibetan Plateau in China, have a fragile ecological environment, complex and sensitive climate, and diverse land-cover types. It plays an important role in the Qinghai-Tibetan Plateau Ecological Barrier and Northern Sand Control Belt in China's two screens and three belts ecological security strategy. Based on land use data of 1980, 1990, 1995, 2000, 2005, 2010, 2015, and 2020, we utilized GIS technology, land use dynamic degree, and land use transition matrixes to analyze the spatial and temporal evolution of land use in the QMs from 1980 to 2020. The results showed the following: (1) From 1980 to 2020, grassland, forest land, and unused land were the main land-use types in the QMs, and the proportion of construction land accounted for only 0.31% of all land-use types. (2) The single land use dynamic degree showed that the dynamic degree of construction land was the highest and the fastest change rate from 2010 to 2015. The comprehensive land use dynamic degree showed that the intensity of land-use change was relatively drastic in the three time periods of 1990-1995, 1995-2000, and 2015-2020. (3) The land-use types in the study area switched infrequently during 2000-2005, 2005-2010, and 2010-2015. (4) The main transition directions of land-use types were grassland and unused land to other land-use types. These changes altered the spatial distributions of different land-use types. The study is critical for understanding the spatial and temporal change patterns of land-use change in the QMs and providing guidance for the optimization of land use in the study area and the improvement of regional eco-environmental protection.

Surface albedo is an important driver of surface processes that promote glacier melting and is a key variable influencing glacier surface melt. Despite much focus in the literature on variations in albedo and its influence on snow surfaces, little attention has been paid to dust and its impact on bare-ice albedo with respect to glacier melting surfaces. In this paper, spatial changes in glacier albedo were investigated using three Landsat images taken during the ablation season in 2006; temporal variations in albedo were measured by an automatic weather station (AWS) in the ablation zone between 26 June and 1 August 2007 at Urumqi Glacier No. 1 in Tien Shan. Ice and snow samples and reflection spectra at 325-1050 nm were collected in August, 2007 at Urumqi Glacier No. 1. The data suggested that spatial changes in glacier albedo are not prominent after snowfall; however, once ice becomes exposed, glacier albedo varies remarkably and generally increases with elevation, especially around the snow line. Temporal variations are characterized by a large range and high frequency, and most are induced by snowfall, changes in cloud conditions, and surface dust; snowfall and cloud increase glacier albedo. Furthermore, the response of snow albedo is more sensitive to cloud compared with the response of ice albedo. Over a bare ice surface, the albedo generally decreases as the concentration of surface dust increases. Organic matter is a primary factor in reducing the albedo over ice.

Snow cover distribution has a profound impact on ground temperature, on thickness of the active layer, and on permafrost. The purpose of this study was to evaluate the effects of snow cover on soil thermal regimes in West Siberia and to characterize the meso- and micro-scale spatial variation of winter ground surface temperature (GST). Maximum snow cover thickness (> 80 cm) and duration (similar to 8 months) were recorded for the lower elevation areas and in the forest site (using a vertical array of Muttons). Shallow snow cover and a late snow formation characterized open raised areas with shallow permafrost. Our results indicate that 20 cm snow cover thickness is the minimum for generating a significant insulating effect. Date of snow cover formation with thickness > 20 cm had the strongest influence on soil temperature regimes. We found a significant negative correlation between winter GST and elevation. This relationship is indirectly controlled by snow cover redistribution. We additionally have shown that elevation, n-factor and winter GST are the variables most significantly affecting thaw depth in permafrost-affected soils. This research dictates the need for taking into account snowfall, and its redistribution due to the variability of local factors, in predicting the effects of climate change on soil temperatures and active layer depth. According to long-term meteorological data for West Siberia, a temporal trend in snowfall is not observed. Nevertheless, considerable interannual fluctuations in snow cover thickness can lead to interannual variations in the soil thermal regimes.

Ground ice is a distinctive feature of permafrost, and its thawing under climate change can alter the regional hydrological and biogeochemical cycles. Spatial variations and determinants of ground ice isotopes are critical to understand subsurface water cycling during freeze-thaw process in the context of climate change, while they are not well known in permafrost region due to lack of field investigation. We examined spatial distributions and controlling factors of ground ice isotopes using data of 8 soil profiles surveyed in permafrost areas of the Qinghai-Tibet Plateau (QTP). The stable isotope values (delta H-2 and delta O-18) of subsurface water on the QTP were higher than those in Arctic tundra ecosystem and East Siberian permafrost region. Isotopic values of water components differed each other, and varied significantly among the sampling sites. The spatial distribution of isotopes was complex. Isotopes generally decreased with depth within the soil profile, implying a general isotope depth gradient across different permafrost-affected areas. Water source, evaporative and freeze-out fractionation, and cryoturbation affect soil water isotopes. Correlation analyses showed that delta H-2 and delta O-18 in soil water positively related to air temperature and soil temperature, while negatively related to soil moisture, depth, active layer thickness, vegetation coverage, elevation, and precipitation. Elevation and soil depth mainly controlled spatial distributions of ground ice isotopes. The results could provide a new insight into soil moisture movement and cycling during freeze-thaw process in the permafrost region of the QTP, which is helpful to understand subsurface water cycle mechanism in the context of permafrost degradation. (C) 2019 Elsevier B.V. All rights reserved.