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Increased CO2 emissions from urban energy consumption pose a significant challenge to regional carbon mitigation policies. In this paper, we integrated two nighttime light (NTL) data: the Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) and the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (NPP) composite data to estimate the energy carbon emissions from 2000 to 2019. Then the spatiotemporal dynamics of carbon footprint and deficit in the Yellow River Basin were analyzed at the provincial, municipal, and county scales combined with NPP data. The study shows that (1) the total amount of energy consumption CO2 emissions in the Yellow River Basin had increased from 1332 Mt in 2000 to 6469 Mt in 2019, but the average annual growth rate slowed down after 2010 from 11.5 to 5.61%. (2) From 2000 to 2018, the provinces with the highest carbon footprint and carbon deficit were concentrated in Inner Mongolia and Shanxi. In 2018, Inner Mongolia's carbon footprint was 1366.91 × 104 km2, accounting for 22.8% of the total. Cities with high carbon footprint were mainly economic centers and energy-intensive areas of various provinces. High-carbon deficit counties were mainly distributed in the western region. In 2018, 954 counties exhibited carbon deficits. (3) The carbon footprint in the Yellow River Basin at the municipal and county scales have a significant spatial correlation. The H–H clusters of the carbon footprint on the municipal scale were distributed in the middle reaches of the Yellow River Basin. At the county scale, the L-L clusters were mainly in Sichuan and eastern Henan regions. Through the analysis of the spatial and temporal evolution of carbon footprint and carbon deficit in the Yellow River Basin, it is significant to measure the degree of comprehensive coordination of carbon sources and sinks in the basin, to grasp the differences in the level of regional carbon emissions, and to promote synergistic regional governance, assist in the formulation of more precise carbon emission reduction policies, and to promote green and high-quality development. [ABSTRACT FROM AUTHOR]

As one of the most vital ecological regions in China, the well-being of the Inner Mongolia section of the Yellow River Basin directly hinges upon comprehending the variations in its ecosystem. The current research puts emphasis on the analysis of single-factor ecological indicators within the Mongolian section of the Yellow River and lacks summarization and analysis regarding the overall state of the ecosystem within the Mongolian section of the Yellow River. This study, using methods such as remote sensing interpretation and model simulation, combined with ground surveys, analyzes the macrostructure, quality status, service functions, and driving factors of the ecosystem in the Inner Mongolia section of the Yellow River Basin from 2000 to 2020. The results indicate that (1) in 2020, the ecosystem structure in the Inner Mongolia section of the Yellow River Basin was predominantly composed of forest, grassland, and other types of systems. (2) From 2000 to 2020, the Normalized Difference Vegetation Index (NDVI), Fractional Vegetation Cover (FVC), and net primary productivity (NPP) all showed increasing trends in the Inner Mongolia section of the Yellow River Basin, with NPP showing a slightly greater increase compared to the NDVI and FVC. (3) Over the past two decades, the overall rate of decrease in the wind erosion modulus per unit area was 1.675 t hm−2. (4) An analysis of the drivers of ecosystem changes revealed that while climate change has exerted an influence, human activities have likewise had a substantial effect on the ecosystem over the past 20 years. This study contributes to a comprehensive understanding of the current status and changes in the ecosystem, providing a decision-making basis for subsequent ecological protection and management projects. [ABSTRACT FROM AUTHOR]

• Taking the high-quality development of the Yellow River basin as the background. • Proposing principles for the initial water rights allocation in Yellow River basin. • Analyzing the priority of Industry water use in the Yellow River basin. • Constructing a model for initial water rights allocation with water-use priorities. • Calculated the initial water rights of Hetao Irrigation District. In September 2019, the Chinese government elevated ecological protection and high-quality development of the Yellow River basin to a major national strategy. However, the scarcity and inequitable distribution of water resources in the basin remain a tough and urgent problem. Therefore, this study probed into the initial water rights allocation (IWRA) of Industry in the Yellow River basin driven by high-quality development. First, based on the status quo of water resources in the basin, this study proposed principles of IWRA of Industry were total quantity control, safeguard, fairness, and efficiency. Next, the paper set the Industry water priority based on the configuration rules, constructed a goal programming model for IWRA of Industry, anticipated the ideal value via the gray model(1,1)(GM (1,1)), and suggested IWRA for end-users through both quota method and water-demand proportion. Last, this study calculated that the initial water rights (IWR) for Hetao Irrigation District in Bayannur city of Inner Mongolia should be 4.38 billion m3. Theories and methods put forward in this paper helps enhance water resources management and improve the high-quality development of the Yellow River basin. [Display omitted] [ABSTRACT FROM AUTHOR]

The urgency of enhancing agricultural productivity within the Yellow River Basin cannot be overstated, given its critical role in ensuring food security amidst the challenges posed by climate change, natural disasters, and the increasing demand for food crops. Utilizing panel data from nine provinces within the Yellow River Basin for the period 2001 to 2020, this study examines the temporal characteristics and spatial distribution of Total Factor Productivity (TFP) for key grain crops—namely wheat, corn, and soybean—through the application of the Malmquist index which can be decomposed through the DEA-Malmquist index methodology. The empirical results demonstrate that TFP growth rates for these crops have exhibited significant phase variations, with soybean recording the highest TFP growth rate in the basin. Additionally, this study underscores marked regional disparities in soybean productivity. TFP decomposition reveals that the primary drivers of TFP improvement across these crops are attributed to technical progress, with gains in overall technical efficiency largely due to scale efficiency enhancements, whereas pure technical efficiency has shown limited progress. Regional analysis indicates that Inner Mongolia leads in TFP growth for all crops, while Ningxia, Sichuan, and Shaanxi lag behind in wheat, corn, and soybean. Additionally, our analysis delineates natural disasters as a significant barrier to Total Factor Productivity (TFP), notably obstructing technological advancements in wheat cultivation. The investigation further reveals a positive relationship between regional per capita income and the growth of wheat TFP, in contrast to a negative relationship with the TFP growth of corn and soybeans. Moreover, investing in agriculture, forestry, water management, and road infrastructure supports the growth of wheat TFP, while urbanization levels pose constraints. Conclusively, an uptick in annual rural electricity usage, along with improved per capita postal and telecommunication services, exerts a favorable influence on TFP for corn and soybeans. [ABSTRACT FROM AUTHOR]

Located in the middle and upper parts of the Yellow River Basin, Qingshuihe County, Inner Mongolia, is a typical hilly and gully loess region and one of areas under the implementation of major ecological protection and restoration projects in the key ecological areas of Yellow River. Scientifically and accurately constructing a soil quality evaluation system for different types of artificial forest land and evaluating their soil quality are essential because they help optimize the structure of artificial forest land and improve the soil quality in the loess hilly area of Yellow River Basin. In this study, soil from four representative types of artificial forest land in the middle and upper reaches of the Yellow River Basin in Inner Mongolia was selected as the study object, with natural non-forest land as the control. Sixteen soil property indices in five classes, namely, soil texture, acid–base properties, moisture, pore, and nutrient, were screened using correlation analysis, minimum dataset (MDS), and principal component analysis methods, and an MDS of soil quality evaluation was constructed. Results showed that (1) the evaluation indices of artificial forest land soil quality based on the MDS included total potassium content, total phosphorus content, alkali-hydrolyzed nitrogen content, total nitrogen content, sand content, moisture content, and non-capillary porosity. (2) No significant differences were observed in the soil quality index among the MDS, total dataset, and significant dataset (SDS), all of which exhibited significant positive correlations. (3) The soil quality of the different types of forest land was sorted from high to low as follows: mixed coniferous and broad-leaved forests, larch forests, mixed arbor and shrub forests, Armeniaca sibirica forests, and natural non-forest land. [ABSTRACT FROM AUTHOR]

Ecological restoration is an important implement to avoid land degradation and improve the sustainability of ecosystems. As a spatial definition of ecological restoration, ecological restoration space (ERS) is recognized to have a positive impact on the environment. However, its spatiotemporal pattern and magnitude of contribution to ecosystem services (ESs) remain uncertain. In this study, an ecological restoration trajectories model was developed to investigate the spatiotemporal pattern and evolution of ERS. The InVEST model and geographically weighted regression were used to evaluate the dynamic relationship between ERS and crucial ESs. Results demonstrated that from 1990 to 2015, the cumulative area of ERS in the Yellow River Basin (YRB) was 184,197.05 km2, with Inner Mongolia, Qinghai, and Shaanxi having the largest distribution. The change in geographical center of three subcategories, forest restoration space (FRS), grassland restoration space (GRS), and shrub restoration space (SRS), showed a pronounced geographical migration. Meanwhile, the distribution of ERS significantly improved the conditions of habitat quality (HQ), carbon storage (CS), and soil conservation (SC) on 75.48%, 71.86%, and 56.75% of the grids, respectively. This study provides a scientific foundation for the ecosystem conservation and land management of the YRB. [ABSTRACT FROM AUTHOR]