The Tibetan Plateau (TP) has important influences on regional and global climate change. Here, we perform an in‐depth study of the relationship between cloud parameters and meteorological factors over the TP. The spatiotemporal variations in cloud cover and cloud optical thickness over the TP during the daytime from 2003 to 2015 are analysed using the Aqua‐MODIS level 2 atmospheric product data MYD06. Results show that the annual average cloud cover over the TP decreases from the southeast to the northwest. The cloud cover of the western TP is highest in spring and lowest in autumn, while the cloud cover of the eastern TP is higher in spring and summer. The cloud covers in most areas of the TP exceed 30% in spring and summer, and the cloud optical thickness in the southeastern TP exceeds 10 in summer, with substantial cloud cover and cloud optical thickness changes. Compared to other seasons, the cooling effect of the near surface cloud net radiative forcing is greater during daytime in summer, which is likely associated with thick cloud optical thickness or large cloud cover. The results of the analysis of relationships among cloud cover, water vapour and air temperature show that positive correlations exist between cloud cover and water vapour, and that significantly negative correlations exist between cloud cover and air temperature over the TP. Combined with the analysis of variation features in the cloud parameters and meteorological factors, we find that water vapour variations during the daytime over the TP lead to cloud cover changes, which affect the air temperature variations over the TP by the cooling effects of clouds, especially in summer.

In recent years, multiple disturbances have significantly altered terrestrial ecosystems in arid and semi-arid regions, particularly on the Mongolian Plateau (MP). Net primary productivity (NPP) of vegetation is an essential component of the surface carbon cycle. As such, it characterizes the state of variation in terrestrial ecosystems and reflects the productive capacity of natural vegetation. This study revealed the complex relationship between the natural environment and NPP in the ecologically fragile and sensitive MP. The modified Carnegie–Ames–Stanford Approach (CASA) model was used to simulate vegetation NPP. Further, the contributions of topography, vegetation, soils, and climate to NPP’s distribution and spatiotemporal variation were explored using the geographic detector model (GDM) and structural equation model (SEM). The study’s findings indicate the following: (1) NPPs for different vegetation types in the MP were in the order of broad-leaved forest > meadow steppe > coniferous forest > cropland > shrub > typical steppe > sandy land > alpine steppe > desert steppe. (2) NPP showed an increasing trend during the growing seasons from 2000 to 2019, with forests providing larger vegetation carbon stocks. It also maintained a more stable level of productivity. (3) Vegetation cover, precipitation, soil moisture, and solar radiation were the key factors affecting NPP’s spatial distribution. NPP’s spatial distribution was primarily explained by the normalized difference vegetation index, solar radiation, precipitation, vegetation type, soil moisture, and soil type ($q$-statistics = 0.86, 0.71, 0.67, 0.67, 0.57, and 0.57, respectively); the contribution of temperature was small ($q$-statistics = 0.26), and topographic factors had the least influence on NPP’s distribution, as their contribution amounted to less than 0.20. (4) A SEM constructed based on the normalized difference vegetation index (NDVI), solar radiation, precipitation, temperature, and soil moisture explained 17% to 65% of the MP’s NPP variations. The total effects of the MP’s NPP variations in absolute values were in the order of NDVI (0.47) > precipitation (0.33) > soil moisture (0.16) > temperature (0.14) > solar radiation (0.02), and the mechanisms responsible for NPP variations differed slightly among the relevant vegetation types. Overall, this study can help understand the mechanisms responsible for the MP’s NPP variations and offer a new perspective for regional vegetation ecosystem management.

The present work is the first systematic and large scale study on radioactive materials and heavy metals in surface soil around the Bayanwula prospective uranium mining area in China. In this work, both natural and anthropogenic radionuclides and heavy metals in 48 surface soil samples were analyzed using High Purity Germanium (HPGe) γ spectrometry and inductively coupled plasma-mass spectrometry (ICP-MS). The obtained mean activity concentrations of ²³⁸U, ²²⁶Ra, ²³²Th, ⁴⁰K, and ¹³⁷Cs were 25.81 ± 9.58, 24.85 ± 2.77, 29.40 ± 3.14, 923.0 ± 47.2, and 5.64 ± 4.56 Bq/kg, respectively. The estimated average absorbed dose rate and annual effective dose rate were 76.7 ± 3.1 nGy/h and 83.1 ± 3.8 μSv, respectively. The radium equivalent activity, external hazard index, and internal hazard index were also calculated, and their mean values were within the acceptable limits. The estimated lifetime cancer risk was 3.2 × 10⁻⁴/Sv. The heavy metal contents of Cr, Ni, Cu, Zn, As, Cd, and Pb from the surface soil samples were measured and their health risks were then assessed. The concentrations of all heavy metals were much lower than the average backgrounds in China except for lead which was about three times higher than that of China’s mean. The non-cancer and cancer risks from the heavy metals were estimated, which are all within the acceptable ranges. In addition, the correlations between the radionuclides and the heavy metals in surface soil samples were determined by the Pearson linear coefficient. Strong positive correlations between radionuclides and the heavy metals at the 0.01 significance level were found. In conclusion, the contents of radionuclides and heavy metals in surface soil around the Bayanwula prospective uranium mining area are at a normal level.

As ecological spaces shrink and ecological environments deteriorate, the tensions between economic development and ecological protection increasingly intensify. How to balance coordination of the layout of ecological spaces with urban land development to maximize the profit of developed land without affecting ecological protection becomes a key issue for urban planners in promoting sustainable development. Based on the minimum cumulative resistance model and by applying a landscape security pattern and economic principles, this paper optimizes urban land development allocation from the comparative advantages of the ecological-economy perspective. The proposed method of optimal land development allocation took into account basic farmland protection and ecological space protection, calculating the end of each land development unit from the ecology-economy comparative advantage perspective. According to the optimization proposal, the city in this case study can be further developed to the west and moderately toward the east and south. The northwestern wetland nature reserves, lakes, and Heihe River have important ecological functions that should be allocated as important ecological protection areas. This provides a scientific method and theoretical basis to determine the size and intensity for optimal land development. Landscape security pattern analysis evaluated the important ecological areas within the region and provided a basis for defining the basic ecological space. At the same time, the land development suitability evaluation identified priorities in a continuous spatial land development scale and provided the basis for the land development spatial layout.

The Mongolian Plateau (MP) has important influences on regional and global climate change. The spatiotemporal variations in the cloud cover and cloud optical thickness of total, high, middle, and low clouds over the MP during the daytime from 2006 to 2015 are analyzed using MODIS level 2 atmospheric data. Results show that the annual average total cloud cover over the MP decreases from the forest area in the northeast to the desert area in the southwest. The total cloud cover over the MP is obviously higher in summer than in other seasons, in which high clouds have a largest proportion, with the substantial total cloud cover changes. The spatial distributions of the high, middle, and low cloud covers over the MP are highly variable. The cooling effect of the cloud net radiative forcing is greater during the daytime in summer than in other seasons, which is likely associated with thick cloud optical thickness or large cloud cover in summer. Combined with the analyses of relationships among cloud cover, cloud optical thickness, cloud radiative forcing, and air temperature, the results show that significantly negative correlations exist between cloud optical thickness and cloud radiative forcing, and between total cloud cover and air temperature in the MP. The decrease in air temperature in summer over the MP during daytime confirm that the increase in the daytime total cloud cover strengthen the cooling effects of clouds and decrease the air temperature, especially in the high-value area with cloud cover distribution over the northeast MP.

The Mongolian Plateau (MP) is among the most sensitive areas to global climate change, and the clouds over the MP have a greater impact on regional and global radiation budgets by altering the atmospheric and surface radiative forcing. In this study, daily Cloud and Earth Radiation Energy System data are used to investigate spatiotemporal variation of cloud radiative forcing (CRF) at the top of atmosphere (TOA), surface and atmosphere over the MP from 2003 to 2017 and then combined with Moderate Resolution Imaging Spectroradiometer level 2 atmospheric data during the same period to analyse the cloud parameter impacts on CRF over the MP. At the TOA and surface, net radiative forcing (NRF) and shortwave radiative forcing (SRF) have cooling effects and longwave radiative forcing (LRF) have heating effects in all four seasons, and the NRF cooling effect in most areas of the MP decreases in summer and autumn and increases in spring and winter. In the atmosphere, SRF in spring and summer and NRF in summer reach larger values and heat the atmosphere, and LRF plays a strong cooling role in winter. The NRF change trend in the atmosphere over Mongolia is noteworthy in spring, its reduction slope is large, and most areas of Mongolia passed a significance test. As expected, a significant negative correlation was observed between cloud cover and NRF (as well as SRF) at the TOA and surface and a positive correlation was observed with NRF/SRF in the atmosphere and all LRF. With the increase in cloud optical thickness and cloud water path, the NRF and SRF cooling effects at the TOA and surface, the LRF cooling effect in the atmosphere, the LRF heating effect at the surface, and the SRF heating effect in the atmosphere all become stronger.