Overall population exposure is measured by multiplying the annual average number of extremely hot days by the number of people exposed to the resultant heat. Extreme heat is also subdivided into high temperature (HT) and extremely high temperature (EHT) in cases where daily maximum temperature exceeds 35℃ and 40℃, respectively. Chinese population exposure to HT and EHT over four periods in the future (i.e., 2021-2040, 2041-2060, 2060-2081 and 2081-2100) were projected at the grid cell level in this study using daily maximum temperature based on an ensemble mean of 21 global climate models under the RCP8.5 scenario and with a population projection based on the A2r socio-economic scenario. The relative importance of population and climate as drivers of population exposure was evaluated at different spatial scales including national and meteorological geographical divisions. Results show that, compared with population exposure seen during 1981-2010, the base period, exposure to HT in China is likely to increase by 1.3, 2.0, 3.6, and 5.9 times, respectively, over the four periods, while concomitant exposure to EHT is likely to increase by 2.0, 8.3, 24.2, and 82.7 times, respectively. Data show that population exposure to HT is likely to increase significantly in Jianghuai region, Southwest China and Jianghan region, in particular in North China, Huanghuai region, South China and Jiangnan region. Population exposure to EHT is also likely to increase significantly in Southwest China and Jianghan region, especially in North China, Huanghuai, Jiangnan, and Jianghuai regions. Results reveal that climate is the most important factor driving the level of population exposure in Huanghuai, Jianghuai, Jianghan, and Jiangnan regions, as well as in South and Southwest China, followed by the interactive effect between population and climate. Data show that the climatic factor is also most significant at the national level, followed by the interactive effect between population and climate. The rate of contribution of climate to national-level projected changes in exposure is likely to decrease gradually from ca. 70% to ca. 60%, while the rate of contribution of concurrent changes in both population and climate is likely to increase gradually from ca. 20% to ca. 40% over the four future periods in this analysis.
Extreme rainstorm and the subsequent flood increasingly threaten the security of human society and ecological environment with aggravation of global climate change and anthropogenic activity in recent years. Therefore, the research on flood mitigation service (FMS) of ecosystem should be paid more attention to mitigate the risk. In this paper, we assessed FMS in the Upper Reaches of Hanjiang River (URHR), China from 2000 to 2014 using the Soil Conservation Service Curve Number (SCS-CN) model, and further simulated the future FMS under two climate scenarios (in 2020 and 2030). The results reveal that the FMS presented a fluctuating rising trend in the URHR from 2000 to 2014. The FMS in southern URHR was higher than that of northern URHR, and the change rate of FMS in the upstream of URHR (western URHR) was higher than the downstream of URHR (eastern URHR). The future FMS under scenarios of Medium-High Emissions (A2) and Medium-Low Emissions (B2) will decrease consistently. As land use/land cover changes in the URHR are negligible, we concluded that the change in FMS was mainly driven by climate change, such as storm and runoff. Our study highlights that climate scenarios analysis should be incorporated into the assessment of hydrologic-related services to facilitate regional water resources management.
Although several previous studies in Inner Mongolia examined the effects of ecological conservation on the delivery of ecosystem services, they were often limited in scope (few ecosystem services were assessed) and often suffered from confounding by spatial variation. In this study, we examined the impact of conservation measures (changes in grassland utilization patterns) on the provision of selected ecosystem services in three types of grasslands (meadow steppe in Hulun Buir, typical steppe in Xilin Gol, and semi-desert steppe in Ordos) in Inner Mongolia. We examined five utilization patterns: no use (natural grasslands), light use, moderate use, intensive use, and recovery sites (degraded sites protected from further use). Through household surveys and vegetation and soil surveys, we measured the differences in ecosystem services among the different grassland utilization patterns. We also identified spatial factors that confounded the quantification of ecosystem services in different types of grasslands. We found that light use generally provided high levels of ecosystem services in meadow steppe and typical steppe, with the main differences in the supporting ecosystem services. Surprisingly, we found no consistently positive impacts of strict conservation activities across the sites, since the results varied spatially and with respect to differences in the land-use patterns. Our study suggests that appropriate grassland utilization patterns can enhance the supply of ecosystem services and reduce negative effects on both household livelihoods and the environment.
Soil erosion has become a major global environmental problem and is particularly acute on the Loess Plateau (LP), China. It is therefore highly important to control this process in order to improve ecosystems, protect ecological security, and maintain the harmonious relationship between humans and nature. We compared the effects of rainfall and land use (LU) patterns on soil erosion in different LP watersheds in this study in order to augment and improve soil erosion models. As most research on this theme has so far been focused on individual study areas, limited analyses of rainfall and LU patterns on soil erosion within different-scale watersheds has so far been performed, a discrepancy which might influence the simulation accuracies of soil erosion models. We therefore developed rainfall and LU pattern indices in this study using the soil erosion evaluation index as a reference and applied them to predict the extent of this process in different-scale watersheds, an approach which is likely to play a crucial role in enabling the comprehensive management of this phenomenon as well as the optimized design of LU patterns. The areas considered in this study included the Qingjian, Fenchuan, Yanhe, and Dali river watersheds. Results showed that the rainfall erosivity factor (R) tended to increase in these areas from 2006 to 2012, while the vegetation cover and management factor (C) tended to decrease. Results showed that as watershed area increased, the effect of rainfall pattern on soil erosion gradually decreased while patterns in LU trended in the opposite direction, as the relative proportion of woodland decreased and the different forms of steep slope vegetation cover became more homogenous. As watershed area increased, loose soil and craggy terrain properties led to additional gravitational erosion and enhanced the effects of both soil and topography.
As the largest developing country in the world, China’s rural areas face many poverty-related issues. It is imperative to assess poverty dynamics in a timely and effective manner in China’s rural areas. Therefore, we used the poverty gap index to investigate the poverty dynamics in China’s rural areas during 2000-2014 at the national, contiguous poor areas with particular difficulties and county scales. We found that China made significant achievements in poverty alleviation during 2000-2014. At the national scale, the number of impoverished counties decreased by 1428, a reduction of 97.28%. The rural population in impoverished counties decreased by 493.94 million people or 98.76%. Poverty alleviation was closely associated with economic development, especially with industrial development. Among all 15 socioeconomic indicators, the industrial added value had the highest correlation coefficient with the poverty gap index (r = -0.458, p<0.01). Meanwhile, the inequality of income distribution in the out-of-poverty counties has been aggravated. The urban-rural income gap among the out-of-poverty counties increased by 1.67-fold, and the coefficient of variation in rural per-capita income among the out-of-poverty counties also increased by 9.09%. Thus, we argued that special attention should be paid to reducing income inequality for sustainable development in China’s rural areas.
Village is an important implementation unit of national poverty alleviation and development strategies of rural China, and identifying the poverty degree, poverty type and poverty contributing factors of each poverty-stricken village is the precondition and guarantee of taking targeted measures in poverty alleviation strategies of China. To respond it, we construct a village-level multidimensional poverty measuring model, and use indicator contribution degree indices and linear regression method to explore poverty factors, while adopting Least Square Error (LSE) model and spatial econometric analysis model to identify the villages’ poverty types and poverty difference. The case study shows that: (1) Spatially, there is obvious territoriality in the distribution of poverty-stricken villages, and the poverty-stricken villages are concentrated in contiguous poverty-stricken areas. The areas with the highest VPI, in a descending order, are Gansu, Yunnan, Guizhou, Guangxi, Hunan, Qinghai, Sichuan, and Xinjiang. (2) The main factors contributing to the poverty of poverty-stricken villages in rural China include road construction, terrain type, frequency of natural disasters, per capita net income, labor force ratio, and cultural quality of labor force. The main causes of poverty include underdeveloped road construction conditions, frequent natural disasters, low level of income, and labor conditions. (3) Chinese poverty-stricken villages include six main subtypes, and most poverty-stricken villages are affected by multiple poverty-forming factors, reflected by a relatively high proportion of the three-factor dominant type, four-factor coordinative type, and five-factor combinative type. (4) There exist significant poverty differences in terms of geographical location and policy support, and the governments still need to carry out targeted poverty alleviation measures according to local conditions. The research can not only draw a macro overall poverty-reduction outline of impoverished villages in China, but also depict the specific poverty characteristics of each village, helping the government departments of poverty alleviation at all levels to mobilize all kinds of anti-poverty resources.
Household CO2 emissions were increasing due to rapid economic growth and different household lifestyle. We assessed per capita household CO2 emissions (PHCEs) based on different household consuming demands (including clothing, food, residence, transportation and service) by using provincial capital city level survey data in China. The results showed that: (1) there was a declining trend moving from eastward to westward as well as moving from northward to southward in the distribution of PHCEs. (2) PHCEs from residence demand were the largest which accounted for 44% of the total. (3) Correlation analysis and spatial analysis (Spatial Lag Model (SLM) and Spatial Error Model (SEM)) were used to evaluate the complex determinants of PHCEs. Per capita income (PI) and household size (HS) were analyzed as the key influencing factors. We concluded that PHCEs would increase by 0.2951% and decrease by 0.5114% for every 1% increase in PI and HS, respectively. According to the results, policy-makers should consider household consuming demand, income disparity and household size on the variations of PHCEs. The urgency was to improve technology and change household consuming lifestyle to reduce PHCEs.
This paper analyses the features and dynamic changes of the spatial layout of air transportation utilization among different provinces in China. It makes use of data for the airport throughput and socio-economic development of every province throughout the country in the years 2006 and 2015, and employs airport passenger and cargo throughput per capita and per unit of GDP as measures of regional air transportation utilization, which is significant for refining indicators of regional air transportation scale and comparing against them. It also analyzes the spatial differences of coupling between the regional air transportation utilization indicators and the key influencing factors on regional air transportation demand and utilization, which include per capita GDP, urbanization rate, and population density. Based on these key influencing factors, it establishes a multiple linear regression model to conduct forecasting of each province’s future airport passenger and cargo throughput as well as throughput growth rates. The findings of the study are as follows: (1) Between 2006 and 2015, every province throughout the country showed a trend of year on year growth in their airport passenger and cargo throughput per capita. Throughput per capita grew fastest in Hebei, with a rise of 780%, and slowest in Beijing, with a rise of 38%. Throughput per capita was relatively high in western and southeastern coastal regions, and relatively low in northern and central regions. Airport passenger and cargo throughput per unit of GDP showed growth in provinces with relatively slow economic development, and showed negative growth in provinces with relatively rapid economic development. Throughput per unit of GDP grew fastest in Hebei, rising 265% between 2006 and 2015, and Hunan had the fastest negative growth, with a fall of 44% in the same period. Southwestern regions had relatively high throughput per unit of GDP, while in central, northern, and northeastern regions it was relatively low. (2) Strong correlation exists between airport passenger and cargo throughput per capita and per capita GDP, urbanization rate, and population density. Throughput per capita has positive correlation with per capita GDP and urbanization rate in all regions, and positive correlation with population density in most regions. Meanwhile, there is weak correlation between airport passenger and cargo throughput per unit of GDP and per capita GDP, urbanization rate, and population density, with positive correlation in some regions and negative correlation in others. (3) Between 2015 and 2025, it is estimated that all provinces experience a trend of rapid growth in their airport passenger and cargo throughput. Inner Mongolia and Hebei will see the fastest growth, rising 221% and 155%, respectively, while Yunnan, Sichuan, and Hubei will see the slowest growth, with increases of 62%, 63%, and 65%, respectively.
From the development of modern transportation to the current era of high-speed transportation networks, the Beijing-Tianjin-Hebei (BTH) region has always played a national leading role in land transportation development of China. In order to explore the long-term evolutionary characteristics of land transportation in the BTH region, this paper utilized a temporal scale of 100 years to systematically interpret the development process of the land transportation network. Taking 13 cities within the BTH region as research anchor cities, we took into account “leaping” mode of transportation in order to investigate the evolution of accessibility. Our research shows the following results: (1) The land transportation network in the BTH region has undergone five stages of development: the initial period of modernization (1881-1937); the period of stagnation of transportation development (1937-1949); the network expansion period (1949-1980); the period of trunk construction (1980-1995), and the period of high-speed transportation network development (1995-present). The network structure centered around Beijing has existed from the outset of modern transportation development. (2) The accessibility spatial pattern of land transportation in BTH region has evolved from expansion along traffic corridors to the formation of concentric circles. The stratified circular structure of transportation in anchor cities has gradually developed into a contiguous development pattern. (3) There are clear hierarchical differences in the transportation structures of anchor cities. Beijing has always been at the top of this hierarchy, while the hierarchical position of Zhangjiakou has fallen noticeably since 1949. The Beijing-Tianjin region was the first region to form a short-duration transportation circle structure, while the transportation advantages of the central part of Hebei Province, which is located in the center of the BTH transportation region, have yet to be realized.
In order to advance land use and land cover change (LUCC) research in Nepal, it is essential to reconstruct both the spatiotemporal distribution of agricultural land cover as well as scenarios that can explain these changes at the national and regional levels. Because of rapid population growth, the status of agricultural land in Nepal has changed markedly over the last 100 years. Historical data is used in this study, encompassing soils, populations, climatic variables, and topography. Data were revised to a series of 30 m grid cells utilized for agricultural land suitability and allocation models and were analyzed using a suite of advanced geographical tools. Our reconstructions for the spatiotemporal distribution of agricultural land in Nepal reveal an increasing trend between 1910 and 2010 (from 151.2 × 102 km2 to 438.8 × 102 km2). This expanded rate of increase in agricultural land has varied between different eco, physiographic, and altitudinal regions of the country, significantly driven by population changes and policies over the period of this investigation. The historical dataset presented in this paper fills an existing gap in studies of agricultural land change and can be applied to other carbon cycle and climate modeling studies, as well as to impact assessments of agricultural land change in Nepal.
Despite many studies on land degradation in the Highlands of Northern Ethiopia, quantitative information regarding long-term changes in land use/cover (LUC) is rare. Hence, this study aims to investigate the LUC changes in the Geba catchment (5142 km2), Northern Ethiopia, over 80 years (1935-2014). Aerial photographs (APs) of the 1930s and Google Earth (GE) images (2014) were used. The point-count technique was utilized by overlaying a grid on APs and GE images. The occurrence of cropland, forest, grassland, shrubland, bare land, built-up areas and water body was counted to compute their fractions. A multivariate adaptive regression spline was applied to identify the explanatory factors of LUC and to create fractional maps of LUC. The results indicate significant changes of most types, except for forest and cropland. In the 1930s, shrubland (48%) was dominant, followed by cropland (39%). The fraction of cropland in 2014 (42%) remained approximately the same as in the 1930s, while shrubland significantly dropped to 37%. Forests shrank further from a meagre 6.3% in the 1930s to 2.3% in 2014. High overall accuracies (93% and 83%) and strong Kappa coefficients (89% and 72%) for point counts and fractional maps respectively indicate the validity of the techniques used for LUC mapping.
