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Adopting conservation tillage technology can promote sustainable agriculture development. There have been many studies on all farmers' conservation tillage behaviors, but few studies are based on a farmer's multidimensional heterogeneity perspective. Given the background, we conduct an empirical evaluation using micro survey data from 819 households in the middle and upper reaches of the Yellow River Basin. This paper uses the entropy method to classify farm households into three types: economically dominant, resource dominant, and socially dominant. Furthermore, we use the Heckman sample selection model to discuss the factors that affect the adoption of conservation tillage technology by different types of farmers. The results show that land fragmentation degree can inhibit economically dominant farmers conservation tillage technology adoption behavior. Social relations can positively influence resource dominant farmers. The share of non-farm income will positively impact socially dominant farmers. This paper further proposes policy implications, based on the findings that different types of farmers have various factors influencing conservation tillage technology adoption behavior. [ABSTRACT FROM AUTHOR]

This paper focuses on the spatiotemporal evolution characteristics, as well as the driving factors, of carbon emissions in the prefecture-level cities in the Yellow River Basin (YB). The paper's findings will aid in promoting ecological conservation and high-quality development in the region. The initiatives undertaken in the YB are a significant national strategy towards achieving carbon peaking and carbon neutrality. To fully investigate the spatiotemporal evolution process, as well as the typical characteristics of their carbon emissions, conventional, and spatial Markov transition probability matrices were developed utilizing YB's panel data for 55 prefecture-level cities from 2003 to 2019. The generalized Divisia index decomposition method (GDIM) cleverly uses this data to conduct a complete analysis of the dynamics and driving processes influencing the change in carbon emissions in these cities. However, the evolution of carbon emissions in prefecture-level cities has reached a point of stability that maintains the original state, making it challenging to make meaningful short-term progress. The data indicates that prefecture-level cities in the YB are emitting more carbon dioxide on average. Neighborhood types in these cities significantly influence the transformation of carbon emissions. Low-emission areas can encourage a reduction in carbon emissions, whereas high-emission areas can encourage an increase. The spatial organisation of carbon emissions exhibits a "high-high convergence, low-low convergence, high-pulling low, low-inhibiting high" club convergence phenomenon. Carbon emissions rise with per capita carbon emissions, energy consumed, technology, and output scale, whereas it falls with carbon technology intensity and output carbon intensity. Hence, instead of enhancing the role of increase-oriented variables, prefecture-level cities in the YB should actively engage these reduction-oriented forces. The YB's key pathways for lowering carbon emissions include boosting research and development, promoting and applying carbon emission reduction technologies, lowering output carbon intensity and energy intensity, and improving energy use effectiveness. [ABSTRACT FROM AUTHOR]

Promoting the green development of resource-based cities is an essential way to achieve sustainable regional economic development. Based on 2009–2019 panel data of the Yellow River Basin cities, this study adopts the super-directional distance function model to measure the green development efficiency of these selected cities. Furthermore, based on the Malmquist-Luenberger index, this paper focuses on the dynamic change trend of green development efficiency and internal driving factors. Furthermore, the Tobit model is used to specifically explore the influencing factors affecting the green development of cities. The findings suggested that the green development efficiency of selected cities falls in the middle to high range and that the efficiency varies among all cities in the Yellow River Basin. Likewise, technical efficiency improvements and technological progress drive development efficiency, and the former contributes more to green development. However, financial development, energy structure adjustments, and environmental regulation can strongly contribute to the green development of cities, and each influencing factor has obvious temporal and regional differences. This paper proposes appropriate policy suggestions to promote the coordinated development of the economic development and environmental protection of the Yellow River Basin. [ABSTRACT FROM AUTHOR]

Assessing and monitoring the green total factor energy efficiency (GTFEE) of cities while considering technology heterogeneity is crucial for the development of energy-conservation and emission-reduction policies. Considering that the heterogeneity of production technologies encompasses several dimensions, this paper proposes a 3E3S (Economy-Environment-Energy-Society-Science-Space) heterogeneity framework and integrates it with the improved meta-frontier global SBM-undesirable to analyze GTFEE and its decomposition. Empirical analysis of cities in the Yellow River Basin of China (YRBC) highlights the following: (1) The 3E3S heterogeneity framework facilitates the classification of all cities into three distinct groups, a finding that contrasts significantly with previous outcomes documented in the literature that relied solely on criteria such as geographic location. (2) The three groups identified under the meta-frontier exhibit substantial energy-saving potentials of 24.49%, 35.17%, and 52.46%, respectively. Additionally, there are spatiotemporal variations in GTFEE, with cities located in the central part of YRBC, particularly those in Shanxi province, demonstrating poor GTFEE performance. (3) The decomposition analysis of GTFEE indicates that technological progress plays a pivotal role in enhancing GTFEE on the whole, albeit with varying approaches for improving GTFEE depending on individual cities. [ABSTRACT FROM AUTHOR]

How to raise the ecological compensation fund for the Yellow River Basin is one of the key difficulties for executing the ecological compensation mechanism and ensuring the high-quality development of the entire basin. This paper, which is based on systems theory, analyzes the social-economic-ecological compound system of the Yellow River Basin. It makes the point that the goals of human-water harmony, ecological compensation efficiency improvement, and coordinated regional development should be achieved in raising ecological compensation funds. Guided by the raising targets, a two-layer fundraising model based on efficiency and fairness is constructed for ecological compensation. The upper-level model is built to calculate the ecological compensation efficiency of each compensation subject from an input–output perspective. The initial fundraising scheme was further determined to implement the efficiency principle. Within the framework of sustainable development theory, the lower-level model adheres to the fairness principle based on efficiency. The social-economic development level of the compensation subject is considered to discriminate and optimize the initial scheme. Additionally, the two-layer model was utilized to conduct an empirical analysis with the data of the Yellow River Basin from 2013 to 2020. The results show that the optimized fundraising scheme is in line with the actual development level of the Yellow River Basin. This study can provide a reference for the fundraising of horizontal ecological compensation and promote the sustainable development of the whole basin. [ABSTRACT FROM AUTHOR]

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]

The Yellow River Basin (YRB) is a typical ecologically fragile area in both the Chinese and global contexts. This paper built a sensitivity-resilience-pressure model to evaluate the ecological vulnerability (EV) of the YRB at the grid and prefecture-level regional scales; explored the spatiotemporal characteristics of EV; and scrutinized the impacts of socioeconomic driving factors on EV. The results showed that (1) at the grid and prefecture-level regional scales, EV decreased from the upper to lower reaches, and high vulnerability was observed in the provincial capital city. Mild and severe vulnerability constituted the main EV types in the YRB. (2) The EV index of the YRB decreased from 2.71 to 2.56 in the study period, indicating that the ecological environment improved in the YRB. The slightly and lightly vulnerable areas experienced shrinking-expansion changes, and the overall areas of these two EV types showed expanding trends, while the areal changes and overall trends of the moderately, severely, and extremely vulnerable areas were contrary to those of the slightly and lightly vulnerable areas. (3) The impacts of socioeconomic driving factors on EV dynamically strengthened with the improvement of the socioeconomic level. After considering the interactions of all socioeconomic factors, the explanatory power of the spatial differentiation of EV was enhanced, and the influence of these factors became more prominent. [ABSTRACT FROM AUTHOR]

Horizontal ecological compensation mechanism provides solutions for cross-domain protection of ecological environment, and the key to its implementation depends on the establishment of a suitable incentive mechanism of economic benefits to influence the conservation behavior of each interest body. This article constructs a horizontal ecological compensation mechanism for the Yellow River Basin through indicator variables to analyze the profitability of the participating subjects. Based on data from 83 cities in the Yellow River Basin in 2019, an empirical study was conducted using a binary unordered logit regression model to examine the regional benefits generated by the horizontal ecological compensation mechanism in the Yellow River Basin. The level of urban economic development and ecological environment management significantly affects the profitability of horizontal ecological compensation mechanisms in the Yellow River basin. The heterogeneity analysis finds that the profitability of the horizontal ecological compensation mechanism in the Yellow River basin is stronger in the upstream central and western regions, which are more likely to produce better ecological compensation benefits as recipients of compensation funds. Governments in the Yellow River Basin should strengthen cross-regional cooperation, continuously improve the capacity building and modernization of ecological and environmental governance in the basin, and provide solid institutional guarantees for environmental pollution management in China. [ABSTRACT FROM AUTHOR]

It is of great significance to study the trends and internal differences of eco-efficiency in the Yellow River Basin for ecological protection and high-quality development of the Yellow River Basin. According to the characteristics of the Yellow River Basin in China, the eco-efficiency evaluation system was constructed, and the super-efficiency slack-based measure (SBM) model and the super-efficiency SBM model of undesired output were used to calculate the eco-efficiency levels of provinces in the Yellow River Basin from 2005 to 2020, and the variation trend and internal differences were analyzed. The results show that when only the expected output was considered, the eco-efficiency of the Yellow River Basin as a whole and each province showed a fluctuating upward trend, but there were obvious differences. Qinghai Province, Sichuan Province, and Ningxia Autonomous Region had high eco-efficiency, while Shaanxi Province, Shanxi Province, and Inner Mongolia Autonomous Region had low eco-efficiency. Compared with only considering the expected outputs, eco-efficiency of Qinghai Province had improved significantly when considering non-expected outputs. The eco-efficiency of Shandong Province and Henan Province had improved significantly after 2016, while the eco-efficiency of the two provinces had decreased significantly before 2016. The eco-efficiency of Shaanxi, Shanxi, Inner Mongolia, Ningxia, and Gansu had declined to varying degrees. Finally, the reasons for the differences in eco-efficiency in various provinces in the Yellow River Basin were analyzed, and suggestions for improving the eco-efficiency of the Yellow River Basin were put forward. [ABSTRACT FROM AUTHOR]

The Yellow River Basin is an energy-rich area. The low-carbon development of the Yellow River Basin is one of the ways to achieve ecological protection and high-quality development. Based on panel data from 2007 to 2019, the dynamic and static carbon emission efficiencies of 98 cities in the Yellow River Basin were calculated using the Undesirable Super Slacks-based model and the Global Malmquist-Luengerber index method, respectively, and the spatial effects of influencing factors were analyzed using the spatial Dubin model. Main conclusions are as follows: (1) The carbon emission efficiency of cities in the Yellow River Basin is different, and only a small numbers of cities have reached the effective state. (2) The main factor for the increase in the overall carbon emission efficiency of the whole Basin is technological progress, and the main factors for the improvement of carbon emission efficiency of different cities are various. (3) The direct effects of economic development level and industrial structure upgrading are significantly positive, the direct effects of technological development level, energy intensity, and opening up are significantly negative, and the indirect effects of population density are positive. The conclusions are of great significance for promoting low-carbon development, ecological protection and high-quality development in the Yellow River Basin. [ABSTRACT FROM AUTHOR]

The Yellow River basin (YRB) is China's most critical energy consumption and coal production area. The improvement of carbon emission reduction efficiency in this area is the key for the Chinese government to achieve the 2030 carbon peak and 2060 carbon neutral ("30.60"). Given this, this study first calculates the carbon emission efficiency of YRB from 2005 to 2019 based on the slack-based measured directional distance function (SBM-DDF) model and combined with Malmquist–Luenberger (ML) index and decomposes the carbon emission efficiency of each province. Then, a panel Tobit model with random effect is constructed to measure the influencing factors and their influence degree of carbon emission efficiency of YRB. Finally, the main influencing factors are selected, and policy suggestions on how to improve the carbon emission efficiency of each province are put forward with the help of the coupling coordination degree (CCD) model. The results show that first, the carbon emission efficiency of each province is significantly different, but it shows a fluctuating upward trend on the whole. Second, the reasons for the rise or decline of the ML index in different provinces are different. Therefore, the development strategies of different provinces should be formulated from the perspective of accelerating technological progress and improving technical efficiency. Finally, the calculation results of influencing factors and coupling coordination degrees show that provinces with high coupling coordination degrees should focus on developing per capita power consumption and controlling per capita power consumption to consolidate the actual urbanization process and industrial structure adjustment. Provinces with low coupling coordination degrees should focus on maintaining the urbanization process and increasing the development of the tertiary industry. Therefore, to fundamentally reduce carbon emissions in YRB areas, we need to consider implementing differentiated emission reduction schemes based on national strategic objectives and in combination with the development characteristics of various provinces. [ABSTRACT FROM AUTHOR]

The problem of imbalanced urban–rural development in China is becoming increasingly serious. Urban–rural integration (URI) is an inevitable way to narrow the urban–rural gap and promote rural development. The Yellow River Basin (YRB) is an important barrier to China's ecological security and plays a crucial role in promoting ecological protection and in high-quality development strategies. Therefore, this article constructs an evaluation index system for URI from five dimensions: economic integration, social integration, ecological integration, element integration, and spatial integration. The simulated annealing-projection pursuit model and time degree are used to analyze the dynamic urban–rural integration level (URIL) of 373 counties from 2000 to 2019. Building upon this foundation, this study classifies four types of URI zones and proposes development strategies tailored to each zone. The results indicate (1) that the URIL in the YRB continues to increase, and that there has been a significant increase in high-level integration areas since 2010. (2) The URIL exhibits a distinct spatial clustering pattern, characterized by lower levels in the upper reaches, and higher levels in the middle and lower reaches. (3) There exists a spatial disparity between economic development and the ecological environment, and it is particularly noticeable in the lower reaches regions. These results contribute to a better understanding of URI in the YRB and provide a reference for the sustainable development of URI in various regions. [ABSTRACT FROM AUTHOR]

Ecological security is the state achieved once an ecosystem maintains its stability under external stress. The Yellow River Basin (YRB) is the largest river basin in northwest and north China and an important area for grain and energy production. The assessment and attribution of ecological security in the YRB are important for protecting the natural environment and ensuring sustainable development. Here, the ecological security of the YRB was assessed by the ecological security index (ESI), a comprehensive index based on the oxygen cycle, and its drivers were attributed to climate change, human activities, vegetation, and soil factors. The spatial pattern of ecological security in the YRB showed high heterogeneity. Ecological insecurity occurred mainly in the middle reaches and regions where the major stream of the Yellow River passes through. The ESI decreased at a rate of − 0.82/year since 2000, which indicated the natural environment continued to be improved in the YRB. Climate change dominated the evolution of ecological security in the upper reaches. The level of ecological security has been improved in the middle reaches after a series of ecological restoration projects conducted. With higher intensity of industrial activity, human activities played a more critical role in ecological security in the lower reaches. Our results suggested that government and local people need to adopt different strategies and actions based on the dominant drivers in the upper, middle, and lower reaches to ensure protection of the natural environment and achieve sustainable development targets. [ABSTRACT FROM AUTHOR]

As a critical way to realize the optimal allocation of water environment capacity resources in the basin, emission rights trading faces multiple uncertainties, making it extremely hard and challenging to formulate appropriate decisions and plans. Therefore, this study uses interval two-stage stochastic programming (ITSP) method to model the emission rights trading process with multiple uncertainties. It can promote the secondary optimal allocation of the emission rights between the demander and the supplier after the initial allocation. Externalities caused by environmental problems are internalized through the form of emission rights trading, thereby reducing the transaction costs and promoting the coordination and integrity of water pollution control among governments in a basin. Finally, the Yellow River basin is taken as an example for case analysis. The results show that the net revenue of emission rights system in the transaction status is better than that in the non-transaction status, and the average gap of net income reaches [171.031, 193.056] billion yuan. Under different reduction policies, the average water pollutant emission reduction in transaction status is [451.15, 628.34] thousand tons, which is generally less than [516.57, 670.05] thousand tons in non-transaction status. As policies get stricter and assimilative capacity of water bodies dwindles, reduction shrinks, leading to higher risks and economic loss from being unable to meet the discharge demand. When reduction policies are relatively loose and assimilative capacity is high, emission rights trading volume peaks. At this time, the trading volume of COD reached [29.05, 40.76] thousand tons, and that of NH3-N reached [3.74, 4.31] thousand tons. All these findings will offer insights for decision-makers on how to strike a balance between economic benefits and emission rights trading plans in the Yellow River basin. [ABSTRACT FROM AUTHOR]

The Yellow River basin (YRB) plays an important role in China's economic and social growth. Based on different dimensions, we adopted the radial basis function (RBF) neural network model and the obstacle degree model to examine the water resource carrying capacity (WRCC) of the YRB. From 2005 to 2020, the WRCC of the entire YRB, as well as the upstream and midstream regions, improved, but the WRCC of the downstream region remained poor, revealing spatial differences. The overall improvement in the WRCC of the Yellow River's nine provinces is good, but the WRCC of Inner Mongolia and Henan is poor, suggesting regional differences. From the standpoint of obstacle factors, the development and usage rate of surface water resources are the main challenges. In 2020, the obstacle degree of the YRB reached 87.4871%. The irrigated area rate in Gansu was the primary obstacle factor, and the obstacle degree reached 73.0238%. Qinghai's industrial aspects mostly hindered the improvement of its WRCC, with an obstacle degree of 31.36%. The results provide a theoretical reference for the high-quality development of the YRB. [ABSTRACT FROM AUTHOR]

The ecological protection and high-quality development of the Yellow River Basin have become major national strategies in China. Therefore, reducing carbon emissions in the Yellow River Basin through efficient industrial agglomeration is necessary for achieving the goals of carbon peak by 2030 and carbon neutrality by 2060. The Yellow River Basin is an important base for energy, chemicals, raw materials, and industry in China, making it important to study the effects of different industrial agglomeration types on carbon productivity from the perspective of agglomeration externalities. Therefore, taking 2009–2019 panel data for prefecture-level cities in the Yellow River Basin, this study uses a spatial Durbin model to investigate the spatial spillover effects of industrial agglomeration (i.e., specialized, diversified, and competitive agglomeration) on carbon productivity. Furthermore, the moderating effects of urbanization level and environmental regulation are analyzed. The results reveal, first, the existence of spatial correlation in carbon productivity across different cities in the Yellow River Basin. Second, diversified and competitive agglomeration significantly increase carbon productivity, although competitive agglomeration has beggar-thy-neighbor spillover effects. Meanwhile, the effect of specialized agglomeration is not significant. Third, the effects of different types of industrial agglomeration differ significantly between cities in different locations and with different resource endowments. Fourth, urbanization level and environmental regulation have different moderating effects in the relationship between different types of industrial agglomeration and carbon productivity. These findings provide evidence for further developing rational industrial agglomeration patterns to enhance carbon productivity in the Yellow River Basin. [ABSTRACT FROM AUTHOR]

Exploring the influencing factors and improvement paths of green water use efficiency (GWUE) based on different regions is very important for the protection and utilization of water resources in the Yellow River Basin (YRB). However, previous studies focused only on the external impact of water use efficiency and did not take into account both internal and external factors. For the zoning of the YRB, the traditional upper, middle, and lower zoning methods were mostly used, and they could not show the impact of climatic and geological conditions. Therefore, based on ecogeographical divisions, the dynamic evolutionary characteristics, regional differences, and internal inefficiencies of green water use efficiency for 48 cities in the YRB from 2008 to 2018 are analyzed using a data envelopment analysis-slack-based measure (DEA-SBM) model, global Malmquist‒Luenberger (GML) index decomposition, and kernel density estimation. We further use a panel Tobit model to analyze the external influencing factors of green water use efficiency and propose ways to improve the utilization of water resources in different regions from both the internal and external perspectives. The results are as follows: (1) During the study period, the GWUE fluctuated between 0.58 and 0.67 and showed a trend of improving in the arid areas and deteriorating in the humid area. (2) Exploring the sources of inefficiency from the internal perspective reveals that the labor redundancy, capital redundancy, and wastewater redundancy in the semihumid area are higher; the energy redundancy in the semiarid area is higher; and the economic output in the arid area is insufficient. (3) From the GML perspective, the absolute difference in the green water use efficiency of the cities in the YRB is expanding. Regarding the technical efficiency (EC) index, the technical efficiency of the semiarid area has a convergence effect. Regarding the technological progress (TC) index, the gap in the arid area has been widening, and the technology in the semihumid and semiarid areas is converging backward. (4) There are significant differences in the external factors affecting GWUE in different ecogeographical regions. This study can help the government consider ecogeographical factors when formulating water resource-related policies, and it provides a scientific reference for how to better utilize water resources in different regions of the YRB from both the internal and external perspectives. [ABSTRACT FROM AUTHOR]

High-quality utilization of land resources (HULR) is critical to the security of land ecosystem and sustainable socioeconomic development. To promote HULR, we explored the spatiotemporal differences and influencing factors of HULR in the Yellow River Basin (an important ecological barrier in China) by using entropy method, spatial panel regression model, and geographically and temporally weighted regression model. We found that the HULR values were 0.22 to 0.28 from 2008 to 2019, showing an increasing trend with obvious spatiotemporal differences. The spatial connectivity, technological innovation, industrialization, industrial upgrading, and marketization are important factors influencing HULR, and different factors have different spatial effects in different regions. Therefore, the important principle of HULR is to pursue the sustainable land utilization within the ecological environment carrying capacity, taking into account the unique ecological and socioeconomic conditions of each region. We hope that our study can provide references for HULR around the world. [ABSTRACT FROM AUTHOR]

The water–energy–food nexus is a complex system where balancing the trade-offs across water, energy, and food sectors is especially difficult in resource-deficient areas. The Yellow River Basin is an area in which water shortages lead to conflicts among water, energy, and food resources. Thus, investigating the evolution state and spatial characteristics of the water–energy–food nexus in the Yellow River Basin is essential for the management of resources and sustainable development orientation of the region's water–energy–food nexus system. This study proposed an integrated assessment framework by using synergy theory and the integrated index system method. The improved Lotka–Volterra symbiotic model was used to elucidate the development and synergy evolution status of the water–energy–food nexus system in prefecture-level cities in the Yellow River Basin between 2004 and 2019. The results show that the order degree of the water and energy subsystems in the Yellow River Basin increased by an average of 0.12 and 0.42, on average respectively, from 2004 to 2019, whereas that of the food subsystem only increased by an average of 0.004 compared to the initial year. Furthermore, most prefecture-level cities experienced subsystem degradation of one or two subsystems during the evolution of the water–energy–food nexus system. Based on the uniqueness and evolution process of each city, there are eight possibilities for system evolution and three types of feedback state between each pair of subsystems, which may lead to a certain spatial aggregation. Additionally, the interaction and competition states are more common than synergy states in the water–energy–food nexus system of the Yellow River Basin. This study provides an important basis and suggestions for the internal relationship and sustainable orientation of water–energy–food nexus systems in such water-deficient areas. [ABSTRACT FROM AUTHOR]

It is an important content of environment management to accurately identify the time change and spatial distribution of net anthropogenic nitrogen inputs (NANI) in the river basin. In order to develop a unified management and diverse control strategy that fits the characteristics of the basin, this study establishes the NANI-S model combining the NANI model with the spatial autocorrelation analysis method, which is a quantification-analysis-control process, and takes the 70 prefecture-cities in the Yellow River Basin (YRB) as the study area. The result shows that (1) the NANI of YRB increased first and then decreased with an average NANI value of 6787.59 kg/(km2·a), showing that the overall N pollution situation of the YRB shows a trend of improvement in nitrogen (N) fertilizer input as the main source, and the average contribution rate was 47.45%. (2) There were obvious spatial differences in the NANI in the YRB because the global Moran's I fluctuated between 0.67 and 0.78. Cities with high NANI clustered in the middle and lower reaches, while low NANI clustered in the upper reaches. (3) Improving fertilizer utilization rate and industrial and domestic sewage treatment capacity was the key point of N control. Based on the results, practical policy recommendations for water pollution management were constructed, which provides a scientific basis for pollution prevention and high-quality development in the basin. In addition, this analysis method can also be applied to other basin N management studies. [ABSTRACT FROM AUTHOR]

Considering the current global goal of carbon neutrality, the relationship between cultivated land intensive use (CLIU) and carbon emission efficiency (CEE) should be explored to address the global climate crisis and move toward a low-carbon future. However, previous work in this has been conducted at provincial/regional scales and few have identified the spatial correlation between CLIU and CEE at the scale of large river basins. Therefore, this study explored the spatiotemporal characteristics of CLIU, cultivated land carbon emissions (CLCE), and CEE, as well as the spatial correlation between CLIU and CEE in the Yellow River Basin (YRB), China. A comprehensive evaluation model, the Intergovernmental Panel on Climate Change (IPCC) coefficient methodology, existing data envelopment analysis model, and bivariate spatial autocorrelation models were used to analyze statistical data from 2005 to 2017. We found that the overall CLIU and CLCE values in the YRB exhibited a continuous increase; the average carbon emission total efficiency and carbon emission scale efficiency first decreased and then increased, and the average carbon emission pure technical efficiency gradually decreased. Areas of high CLCE were concentrated in eastern areas of the YRB, whereas those of high CLIU, carbon emission total efficiency, carbon emission scale efficiency, and carbon emission pure technical efficiency predominantly appeared in the eastern areas, followed by central and western areas of the YRB. Spatial analysis revealed a significant spatial dependence of CLIU on CEE. From a global perspective, the spatial correlations between CLIU and CEE changed from positive to negative with time. Moreover, the aggregation degree between CLIU and CEE gradually decreases with time, while the dispersion degree increases with time, and the spatial correlation gradually weakens. The local spatial autocorrelation further demonstrates that the number of high–low and low–high clusters between CLIU and CEE gradually increases over time, while the number of high–high and low–low clusters gradually decreased over time. Collectively, these findings can help policymakers formulate feasible low-carbon and efficient CLIU policies to promote win–win cooperation among regions. [ABSTRACT FROM AUTHOR]

A better understanding of the spatial coordination relationship between tourism urbanisation and resources environment carrying capacity (RECC) is vital for the regional selection of key eco-liveable tourist cities in the Yellow River Basin. This study addressed this research issue by evaluating and partitioning tourism urbanisation level and RECC of the Yellow River Basin in 2005, 2011, and 2018 using a geographic information system (GIS) technology, spatial autocorrelation model, and partition method. Empirical results suggest that the tourism urbanisation level of Shaanxi Province maintains its leading position, while Shanxi Province has great development potential. The high-value areas of RECC are concentrated in Gansu, Inner Mongolia, and Shandong provinces. The degree of spatial agglomeration of the tourism urbanisation level and RECC has been improved. The RECC exhibits a greater restrictive effect on the current high-level areas of tourism urbanisation, and the spatial correspondence between them is weak. Based on the findings of this study, a series of optimisation strategies have been proposed to promote the sustainable development of tourism urbanisation in the Yellow River Basin. [ABSTRACT FROM AUTHOR]

At present, China's economic development has entered a "new normal." Exploring industrial ecological efficiency (IEE) in the background of economic transformation is of great significance to promote China's industrial transformation and upgrading and achieving high-quality economic development. Based on the super-efficiency DEA model, this study evaluated the IEE of cities in the Yellow River Basin from 2008 to 2017. Exploratory spatial data analysis methods were used to explore the spatial-temporal evolutionary characteristics, and a panel regression model was established to explore the influencing factors of IEE. The research results showed that the IEE in the Yellow River Basin exhibited an elongated S-shaped evolutionary trend from 2008 to 2017, and the mean IEE of cities presented a trend, whereby Yellow River Basin's regions could be ranked in the following order: lower reaches > middle reaches > upper reaches. There was significant spatial autocorrelation of the IEE in the Yellow River Basin, and the hot and cold spots showed an obvious "spatial clubs" phenomenon. The results of panel regression show that the influence factors of IEE in the Yellow River Basin showed spatial heterogeneity in their effect. [ABSTRACT FROM AUTHOR]

Social and economic development processes require large amounts of natural resources and in some cases seriously deteriorate river water quality. Since the reform and expansion era began, China has vigorously pursued socioeconomic development but neglected environmental protection. However, in recent years, improvements in environmental awareness and the implementation of environmental protection measures have led to a balanced relationship between economic development and the environment. In this study, the Yangtze River Basin and the Yellow River Basin were selected as research areas. We used a combination of canonical correlation analysis (CCA) and a distance-based influence assessment method to quantitatively assess the influence of socioeconomic development on river water quality. The results revealed a strong correlation between socioeconomic development and river water quality. The degree of influence of socioeconomic development on water quality varied not only temporally but also spatially due to differences in socioeconomic development and hydrometeorology in the two basins in North and South China. The average degree of influence in the Yangtze River Basin was between 0.22 and 0.27, and that in the Yellow River Basin was between 0.2 and 0.36. Moreover, the degree of influence in the Yangtze River Basin in the wet season was greater than that in the dry season, whereas the opposite pattern was observed in the Yellow River Basin. The degree of influence in both basins gradually declined after 2011, indicating that the coupling and coordination between socioeconomic development and environmental protection have continuously improved and that the water quality has gradually improved. By analysing the influences of various socioeconomic indicators on water quality, we found that the main factors that influence water quality are per capita GDP and urbanization rate in the Yangtze River Basin and urbanization rate in the Yellow River Basin. The results provide a basis for future sustainable development in the Yangtze River Basin and the Yellow River Basin. [ABSTRACT FROM AUTHOR]