The heating effect (or mass elevation effect, MEE) of the Tibetan Plateau (TP) is intense due to its massive body. Some studies have been undertaken on its role as the heat source in summer and its implications for Asian climate, but little has been known of the implications of its MEE for the distribution of mountain altitudinal belts (MABs). Using air temperature data observed and remotely sensed data, MAB/treeline data, and ASTER GDEM data, this paper compares the height of MABs and alpine treelines in the main TP and the surrounding mountains/lowland and explains the difference from the point of view of MEE. The results demonstrate: 1) at same elevation, air temperature and the length of growing season gradually increase from the eastern edge to the interior TP, e.g., at 4500 m (corresponding to the mean altitude of the TP), the monthly mean temperature is 3.58°C higher (April) to 6.63°C higher (June) in the interior plateau than in the Sichuan Basin; the 10°C isotherm for the warmest month goes upward from the edge to the interior of the plateau, at 4000 m in the Qilian Mts. and the eastern edges of the plateau, and up to 4600-5000 m in Lhasa and Zuogong; the warmth index at an altitude of 4500 m can be up to 15°C·month in the interior TP, but much lower at the eastern edges. 2) MABs and treeline follow a similar trend of rising inwards: dark-coniferous forest is 1000-1500 m higher and alpine steppe is about 700-900 m higher in the interior TP than at the eastern edges.
Based on the daily reanalysis data released by NCEP/NCAR and the daily precipitation of 753 Chinese stations from May to August during the period of 1960 to 2012, the statistical characteristics of the cold vortex in northeastern China were analyzed. In addition, the strength index, which described the characteristics of the vortex consistently and frequently, and the geographical distribution were given by continuous anomalies of circulation. Based on this index, the activity routines of the cold vortex, characteristics of atmospheric circulation, and their effects on precipitation in northeastern China were analyzed. The results show that: the activities of the cold vortex exhibit remarkable features of annual and interdecadal oscillation, and the vortex high frequency and its characteristics of atmospheric circulation are described more accurately by the strength index of the cold vortex, which shows a high correspondence with the vortex precipitation during early summer and midsummer in the northeast. In strong (weak) vortex years, the general circulation in the middle and high latitudes of Eurasia is to the advantage (disadvantage) of the formation, development and maintenance of the cold vortex, thus it is easy (difficult) to form the circulation which is beneficial to transmit vapor from south to north during the period of July to August. Blocking over the Ural Mountains prevails (does not prevail) in early summer, and blocking over the Sea of Okhotsk prevails (does not prevail) in midsummer. Areas where the subtropical high is too small (large) and moves toward the north too late (early) are better (worse) for the maintenance of the cold vortex in northeastern China.
The objective of this study was to investigate the concentration and spatial distribution patterns of 9 potentially toxic heavy metal elements (As, Cd, Co, Cr, Pb, Cu, Zn, Mn, and Ni) in road dust in the Bayan Obo Mining Region in Inner Mongolia, China. Contamination levels were evaluated using the geoaccumulation index and the enrichment factor. Human health risks for each heavy metal element were assessed using a human exposure model. Results showed that the dust contained significantly elevated heavy metal elements concentrations compared with the background soil. The spatial distribution pattern of all tested metals except for As coincided with the locations of industrial areas while the spatial distribution of As was associated with domestic sources. The contamination evaluation indicated that Cd, Pb, and Mn in road dust mainly originated from anthropogenic sources with a rating of “heavily polluted” to “extremely polluted,” whereas the remaining metals originated from both natural and anthropogenic sources with a level of “moderately polluted”. The non-cancer health risk assessment showed that ingestion was the primary exposure route for all metals in the road dust and that Mn, Cr, Pb, and As were the main contributors to non-cancer risks in both children and adults. Higher HI values were calculated for children (HI=1.89), indicating that children will likely experience higher health risks compared with adults (HI=0.23). The cancer risk assessment showed that Cr was the main contributor, with cancer risks which were 2-3 orders of magnitude higher than those for other metals. Taken in concert, the non-cancer risks posed by all studied heavy metal elements and the cancer risks posed by As, Co, Cr, Cd, and Ni to both children and adults in Bayan Obo Mining Region fell within the acceptable range.
Slope spectrum has been proved to be a significant methodology in revealing geomorphological features in the study of Chinese loess terrain. The determination of critical areas in deriving slope spectra is an indispensable task. Along with the increase in the size of the study area, the derived spectra are becoming more and more alike, such that their differences can be ignored in favor of a standard. Subsequently, the test size is defined as the Slope Spectrum Critical Area (SSCA). SSCA is not only the foundation of the slope spectrum calculation but also, to some extent, a reflection of geomorphological development of loess relief. High resolution DEMs are important in extracting the slope spectrum. A set of 48 DEMs with different landform areas of the Loess Plateau in northern Shaanxi province was selected for the experiment. The spatial distribution of SSCA is investigated with a geo-statistical analysis method, resulting in values ranging from 6.18 km2 to 35.1 km2. Primary experimental results show that the spatial distribution of SSCA is correlated with the spatial distribution of the soil erosion intensity, to a certain extent reflecting the terrain complexity. The critical area of the slope spectrum presents a spatial variation trend of weak-strong-weak from north to south. Four terrain parameters, gully density, slope skewness, terrain driving force (Td) and slope of slope (SOS), were chosen as indicators. There exists a good exponential function relationship between SSCA and gully density, terrain driving force (Td) and SOS and a logarithmic function relationship between SSCA and slope skewness. Slope skewness increases, and gully density, terrain driving force and SOS decrease with increasing SSCA. SSCA can be utilized as a discriminating factor to identify loess landforms, in that spatial distributions of SSCA and the evolution of loess landforms are correlative. Following the evolution of a loess landform from tableland to gully-hilly region, this also proves that SSCA can represent the development degree of local landforms. The critical stable regions of the Loess Plateau represent the degree of development of loess landforms. Its chief significance is that the perception of stable areas can be used to determine the minimal geographical unit.
During the past decade, great efforts have been made to boost the land use transformation in the Loess Plateau, especially for reducing soil erosion by vegetation restoration measures. The Grain-for-Green project (GFG) is the largest ecological rehabilitation program in China, which has a positive impact on the vegetation restoration and sustainable development for the ecologically fragile region of west China. Based on the Landsat TM/ETM images for three time periods (2000, 2005 and 2010), this study applied the GIS technology and a hill-slope analytical model to reveal the spatio-temporal evolutional patterns of returning slope farmland to grassland or woodland in Baota District, Yan’an city of Shaanxi province. Results showed that: (1) from 2000 to 2010, the area of farmland decreased by approximately 35,030 ha, which is the greatest decrease among all the land-use types, whereas grassland, woodland and construction land increased, of which grassland expanded rapidly by 26,380 ha. (2) The annual variation rate of land-use dynamics was 1.98% during the period 2000-2010, of which the rate was 1.05% for the 2000-2005 period and 2.92% for the 2005-2010 period, respectively. Over the past decade, returning farmland to woodland or pastures was the main source of increased grassland and woodland, and the reduction of farmland contributed to the increase in grassland and woodland by 97.39% and 85.28%, respectively. (3) As the terrain slope increases, farmland decreased and woodland and grassland increased significantly. Areas with a slope ranging from 15° to 25° and less than 15° were the focus of the GFG project, accounting for 85% of the total area of farmland reduction. Meanwhile, the reduction in farmland was significant and spatially correlated with the increase in woodland and grassland. (4) Between 2000 and 2010, the area of destruction of grass and trees in grasslands and woodlands for the reclamation of farmland was approximately 4596 ha. The area subject to the GFG policy was 4456 ha with a slope greater than 25° over the decade, but the area of farmland was still 10,357 ha in 2010. Our results indicate that there has still a great potential for returning the steep-slope farmlands to woodlands or grasslands in the Loess Plateau.
Detailed analysis of Land Use/Land Cover (LULC) using remote sensing data in complex irrigated basins provides complete profile for better water resource management and planning. Using remote sensing data, this study provides detailed land use maps of the Lower Chenab Canal irrigated region of Pakistan from 2005 to 2012 for LULC change detection. Major crop types are demarcated by identifying temporal profiles of NDVI using MODIS 250 m × 250 m spatial resolution data. Wheat and rice are found to be major crops in rabi and kharif seasons, respectively. Accuracy assessment of prepared maps is performed using three different techniques: error matrix approach, comparison with ancillary data and with previous study. Producer and user accuracies for each class are calculated along with kappa coefficients (K). The average overall accuracies for rabi and kharif are 82.83% and 78.21%, respectively. Producer and user accuracies for individual class range respectively between 72.5% to 77% and 70.1% to 84.3% for rabi and 76.6% to 90.2% and 72% to 84.7% for kharif. The K values range between 0.66 to 0.77 for rabi with average of 0.73, and from 0.69 to 0.74 with average of 0.71 for kharif. LULC change detection indicates that wheat and rice have less volatility of change in comparison with both rabi and kharif fodders. Transformation between cotton and rice is less common due to their completely different cropping conditions. Results of spatial and temporal LULC distributions and their seasonal variations provide useful insights for establishing realistic LULC scenarios for hydrological studies.
China has been experiencing an unprecedented urbanization process. In 2011, China’s urban population reached 691 million with an urbanization rate of 51.27%. Urbanization level is expected to increase to 70% in China in 2030, reflecting the projection that nearly 300 million people would migrate from rural areas to urban areas over this period. At the same time, the total fertility rate of China’s population is declining due to the combined effect of economic growth, environmental carrying capacity, and modern social consciousness. The Chinese government has loosened its “one-child policy” gradually by allowing childbearing couples to have the second child as long as either of them is from a one-child family. In such rapidly developing country, the natural growth and spatial migration will consistently reshape spatial pattern of population. An accurate prediction of the future spatial pattern of population and its evolution trend are critical to key policy-making processes and spatial planning in China including urbanization, land use development, ecological conservation and environmental protection. In this paper, a top-down method is developed to project the spatial distribution of China’s future population with considerations of both natural population growth at provincial level and the provincial migration from 2010 to 2050. Building on this, the spatial pattern and evolution trend of Chinese provincial population are analyzed. The results suggested that the overall spatial pattern of Chinese population will be unlikely changed in next four decades, with the east area having the highest population density and followed by central area, northeast and west area. Four provinces in the east, Shanghai, Beijing, Tianjin and Jiangsu, will remain the top in terms of population density in China, and Xinjiang, Qinghai and Tibet will continue to have the lowest density of population. We introduced an index system to classify the Chinese provinces into three categories in terms of provincial population densities: Fast Changing Populated Region (FCPR), Low Changing Populated Region (LCPR) and Inactive Populated Region (IPR). In the FCPR, China’s population is projected to continue to concentrate in net immigration leading type (NILT) area where receives nearly 99% of new accumulated floating population. Population densities of Shanghai, Beijing, Zhejiang will peak in 2030, while the population density in Guangdong will keep increasing until 2035. Net emigration leading type (NELT) area will account for 75% of emigration population, including Henan, Anhui, Chongqing and Hubei. Natural growth will play a dominant role in natural growth leading type area, such as Liaoning and Shandong, because there will be few emigration population. Due to the large amount of moving-out labors and gradually declining fertility rates, population density of the LCPR region exhibits a downward trend, except for Fujian and Hainan. The majority of the western provinces will be likely to remain relatively low population density, with an average value of no more than 100 persons per km2.
This study has revealed spatial-temporal changes in Recreational Business Districts (RBDs) in Beijing and examined the relationship between the location of urban RBDs and traffic conditions, resident and tourist density, scenic spots, and land prices. A more reasonable classification of urban RBDs (LSC, CPS, and ULA) is also proposed. Quantitative methods such as Gini Coefficient, Spatial Interpolation, Kernel Density Estimation, and Geographical Detector were employed to collect and analyze the data from three types of urban RBDs in Beijing in 1990, 2000, and 2014, respectively, and the spatial-temporal patterns as well as the distribution characteristics of urban RBDs were analyzed using ArcGIS software. It was concluded that (1) both the number and scale of urban RBDs in Beijing have been expanding and the trend for all types of urban RBDs in Beijing to be spatially agglomerated is continuing; (2) the spatial-temporal evolution pattern of urban RBDs in Beijing is “single-core agglomeration-dual-core agglomeration-multi-core diffusion”; and (3) urban RBDs were always located in areas with low traffic density, tourist attractions, high resident and tourist population density, and relatively high land valuations; these factors also affect the scale size of RBDs.