ABSTRACT
BACKGROUND: Conducting an extensive study on the spatial heterogeneity of the overall carbon budget and its influencing factors and the decoupling status of carbon emissions from economic development, by undertaking simulation projections under different carbon emission scenarios is crucial for China to achieve its targets to peak carbon emissions by 2030 and to achieve carbon neutrality by 2060. There are large disparities in carbon emissions from energy consumption, the extent of land used for carbon absorption, and the status of decoupling of emissions from economic development, among various regions of China. RESULTS: Based on night light data and land use data, we investigated carbon budget through model estimation, decoupling analysis, and scenario simulation. The results show that the carbon deficit had a continuous upward trend from 2000 to 2018, and there was a significant positive spatial correlation. The overall status of decoupling first improved and then deteriorated. Altogether, energy consumption intensity, population density of built-up land, and built-up land area influenced the decoupling of carbon emissions from economic development. There are significant scenarios of carbon emissions from energy consumption for the study area during the forecast period, only in the low-carbon scenario will the study area reach the expected carbon emissions peak ahead of schedule in 2027; the peak carbon emissions will be 6479.27 million tons. CONCLUSIONS: China's provincial-scale carbon emissions show a positive correlation with economic development within the study period. It is necessary to optimize the economic structure, transforming the economic development mode, and formulating policies to control the expansion of built-up land. Efforts must be made to improve technology and promote industrial restructuring, to effectively reduce energy consumption intensity.
ABSTRACT
Soil erosion has a severe impact on habitat and productivity. It is considered to be a major environmental threat prevalent in ecosystems. However, few researchers have studied the spatial distribution of soil erosion intensity among different geographic environmental factors. The Qin River Basin is a geographical unit consisting of mountains, hills, and plains with significant regional characteristics, and it has a basin area of 14,810.91 km2. This study uses the Geographical Information Systems, Revised Universal Soil Loss Equation model to analyze the spatiotemporal changes in the soil-erosion intensity in the Qin River Basin from 1990 to 2018. Different environmental factors of land use, slope and altitude on erosion intensities of 19 secondary land types were analyzed. It can better reflect the soil erosion under different environmental factors and different land use types. Results show that the soil erosion modulus of Qin River Basin were 10.25 t hm-2 a-1, and it belong to slight erosion from 1990 to 2018. Soil erosion intensity is greater in grassland and woodland than in cropland. The strongest soil erosion occurred in the sparse forestland, and the lowest was in beach land. Soil erosion was the highest for a slope of 15~25° and an altitude of 1200~1500 m. Rainfall and slope are important factors lead to soil erosion, indicating weak water and soil conservation implemented in these areas. Therefore, priority should be given to these geomorphic units to formulate and implement soil-erosion control and ecological restoration policies in the Qin River Basin. This study provides a good reference for preventing and controlling soil erosion in river basins.
Subject(s)
Rivers , Soil Erosion , China , Conservation of Natural Resources , Ecosystem , Environmental Monitoring/methods , Soil , WaterABSTRACT
Climate is a dominant factor affecting the potential geographical distribution of species. Understanding the impact of climate change on the potential geographic distribution of species, which is of great significance to the exploitation, utilization, and protection of resources, as well as ecologically sustainable development. Betula platyphylla Suk. is one of the most widely distributed temperate deciduous tree species in East Asia and has important economic and ecological value. Based on 231 species distribution data points of Betula platyphylla Suk. in China and 37 bioclimatic, soil, and topography variables (with correlation coefficients < 0.75), the potential geographical distribution pattern of Betula platyphylla Suk. under Representative Concentration Pathway (RCP) climate change scenarios at present and in the 2050s and 2070s was predicted using the MaxEnt model. We analyzed the main environmental variables affecting the distribution and change of suitable areas and compared the scope and change of suitable areas under different climate scenarios. This study found: (1) At present, the main suitable area for Betula platyphylla Suk. extends from northeastern to southwestern China, with the periphery area showing fragmented distribution. (2) Annual precipitation, precipitation of the warmest quarter, mean temperature of the warmest quarter, annual mean temperature, and precipitation of the driest month are the dominant environmental variables that affect the potential geographical distribution of Betula platyphylla Suk. (3) The suitable area for Betula platyphylla Suk. is expected to expand under global warming scenarios. In recent years, due to the impact of diseases and insect infestation, and environmental damage, the natural Betula platyphylla Suk. forest in China has gradually narrowed. This study accurately predicted the potential geographical distribution of Betula platyphylla Suk. under current and future climate change scenarios, which can provide the scientific basis for the cultivation, management, and sustainable utilization of Betula platyphylla Suk. resources.
Subject(s)
Climate Change , Ecosystem , Betula , ChinaABSTRACT
The measurement of eco-efficiency is an important tool to evaluate the level of urban sustainable development. Therefore; improving urban eco-efficiency in the lower reaches of the Yellow River ensures the implementation of ecological protection and high-quality development strategies in the Yellow River Basin. In this study; the dynamic changes of urban eco-efficiency and spatiotemporal differences in the lower reaches of the Yellow River were investigated using the Super-SBM (Super-Slack measure model) model with undesirable outputs and standard deviation ellipse. The STIRPAT (Stochastic Impacts by Regression Population; Affluence and Technology) model was introduced to analyze the factors affecting the change in urban eco-efficiency. The results showed that the overall urban eco-efficiency in the lower reaches of the Yellow River has not reached the optimal level. The overall eco-efficiency in the lower reaches of the Yellow River in Shandong Province was higher than that in Henan Province but the gap is narrowing. The spatial differentiation of urban eco-efficiency in the lower reaches of the Yellow River showed the following trends: "blooming in the middle and reverse development at both ends" in the high-value area and gradual decrease in the low-value area. From 2007 to 2018; a direction was notable with respect to the development of urban eco-efficiency in the lower reaches of the Yellow River; with the centripetal force weakening. Although the mean center of urban eco-efficiency located in Shandong Province; it notably shifted to the west during the study period. In terms of driving factors; affluence and technological progress play positive roles in driving eco-efficiency; while investment intensity; industrial structure; and foreign investment intensity hindered the optimization and improvement of urban eco-efficiency in the lower reaches of the Yellow River. The results of this study show that urban eco-efficiency in the lower reaches of the Yellow River is improving; but the regional coordination is poor. The main methods promoting the sustainable development in the study area include changing the mode of extensive investments and the introduction of foreign capital; which improve the energy efficiency and promote faster and better economic development.
