Urbanization has an important effect on ecosystem services (ESs) and identifying the relationship between urbanization and ESs can provide a decision-making reference for regional ecological protection and management. Taking the areas along the Yellow River of Henan Province (AYRHP) as a research area, a coupling system of ESs and urbanization is established in this study to reveal the coupling relationship between the two. ESs are estimated by using Carnegie–Ames–Stanford approach, revision universal soil loss equation, and Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) models. The urbanization level is evaluated from three dimensions, namely, population, economy, and land. The coupling coordination relationship between various ESs and urbanization in AYRHP is quantified from 2000 to 2018 on the county scale based on the coupling coordination degree (CCD) model. The lead–lag relationship between ESs and urbanization is identified by using the relative development degree model, and ecological management zoning is conducted. Results show that in the study period, net primary production (NPP), soil conservation, and food production are increased, whereas water yield is decreased. In the study period, population, economy, and land urbanization level are increasing, and the comprehensive urbanization level is increased by 51.63%. The total CCD between NPP, food production, and water yield and comprehensive urbanization is basic or moderate coordination, whereas that between soil conservation and comprehensive urbanization is moderate maladjustment. In the research period, the coupling coordination between NPP and food production and comprehensive urbanization is increasing; that between water yield and comprehensive urbanization is fluctuated; and that between soil conservation and comprehensive urbanization is decreasing. The result of the research into the relative development degree in 2018 showed that food production, water yield, and soil conservation lag behind the urbanization level in most regions and counties along the Yellow River of Henan Province. On the basis of the lead–lag relationship between different ESs and urbanization level, the AYRHP are divided into ecological reconstruction area, ecological and agricultural improvement area, and ecological conservation area. CCD and relative development degree models can be used to evaluate the coordination relationship between ESs and urbanization, which provides scientific support for regional ES management.

The rapid urbanization and population growth in China have brought the issues of social equity and justice to the forefront. The supply and layout of public service facilities play a crucial role in determining the residents’ quality of life and have become a significant factor triggering social equity and justice concerns. This study took Zhengzhou’s urban core as an example. From the perspectives of regional equality, spatial equity, and social justice, the service area analysis and Gaussian two-step floating catchment area method were used to analyze the public service facilities’ layout situation and the equity and justice issue and to discuss the causes of the current situation. The study found that the social equity and justice of public facilities in Zhengzhou’s urban core were more prominent. The accessibility of public facilities inside and outside the 3rd ring road of the urban core exhibited marked differences, indicating a need for improvement in regional equality and spatial equity. Vulnerable groups lacked special care and public facilities lacked justice. Combined with the development process of urbanization in Zhengzhou, this paper argued that this was closely related to the government’s public policies.

In order to achieve the coordinated development of ecological protection and cultivated land use, ecological security and cultivated land use functions (CLUFs) in the study area were evaluated by constructing a comprehensive evaluation index system. The leading CLUFs were measured, and it was determined to use the normalized revealed comparative advantage (NRCA) index. The spatial superposition analysis of the ecological security level and the leading CLUFs was carried out to obtain the zoning of the coordinated development of ecological security and cultivated land use, and differentiated utilization strategies were proposed for different zones. The results of this study showed the following: (1) The ecological security level of cultivated land in Yuanyang County can be divided into high, medium, and low security levels, accounting for 30.68%, 43.42%, and 25.9% of the total cultivated land area, respectively. The overall ecological security level is high. (2) The current cultivated land use mainly has a production function, accounting for 38.39% of the total cultivated land area, the leading CLUFs that are 34.16% of the cultivated land are the ecological function, and 27.45% of the cultivated land is the living function. (3) The spatial superposition analysis of the ecological security level and leading CLUFs yielded four zones of cultivated land use enhancement, including a production core zone, and different control strategies were proposed for the different zones. These strategies may help to fully realize the multifunctionality of the cultivated land without compromising ecological protection. Implementing differentiated protection for cultivated land in different use zones can achieve the coordinated development of ecological protection and cultivated land use, thus promoting the sustainable use of cultivated land resources.

The unique high/cold environment of the Qinghai–Tibet Plateau (QTP) limits the natural distribution of the population living there and threatens local residents’ health. Thus, exploring the quality of human settlements in this area is of great significance. In this study, 5 first-level indicators and 25 second-level indicators were initially selected, and the entropy TOPSIS method was used to determine the weight of each indicator and evaluate the quality of the human settlements in each county of the QTP. Then, the coefficient of variation and spatial autocorrelation were used to analyze the spatial differences in human settlement quality. Finally, the obstacle degree model was used to identify those obstacles that affect the quality of the human settlements in the QTP. This study has gathered important findings. (1) The human settlement quality in these counties can be divided into 18 high-level areas, 45 mid- and high-level areas, 44 mid-level areas, 79 mid- and low-level areas, and 28 low-level areas. (2) In terms of spatial patterns, the north is higher than the south, the east is slightly higher than the west, and the surrounding area is higher than the interior. (3) In the clustering model, the high–high clustering trend is mainly concentrated in the north of the QTP, whereas the south-central part of the QTP and the zone where Tibet, Qinghai, and Sichuan meet exhibit obvious low–low clustering. (4) The variability of human settlement quality occurs in the order of Sichuan < Yunnan < Gansu < Xinjiang Autonomous Region < Tibet Autonomous Region < Qinghai. (5) The main first-level obstacles affecting human settlement quality in the counties of the QTP are living conditions, construction level of public service facilities, and infrastructure. The main second-level obstacles are the number of living service facilities, the number of residential districts, and the density of the road networks.

A watershed ecosystem is a compound ecosystem composed of land and rivers, and its health is closely related to the sustainable development of the region it is located in. The Yihe River Basin (YRB) in central China’s Henan province, which is located in the north–south transition zone and has a mountain–hill–plain landscape from the upstream to the downstream, is adopted as the research area in this study. A watershed ecosystem health assessment system is constructed based on an ecosystem vigor–organization–resilience–service supply and demand harmony (EVORSH) framework and utilized to assess the ecosystem health in the YRB by taking a 3 km × 3 km grid as the evaluation unit. Thirteen factors are selected from natural and human social factors, and from them, the factors that influence watershed ecosystem health through the generation of spatial heterogeneity are identified using the geographical detector model. The following findings are obtained. (1) The mean value of ecosystem health levels in the YRB is 0.65 and at the good level. The ecosystem health has considerable spatial heterogeneity. The areas with high–high concentration are distributed in the mountains in the upper reaches of the YRB, and the areas with low–low concentration are mainly distributed in the plain areas in the middle reaches of the YRB. (2) The geographical detector result shows that 9 of 13 factors have a considerable impact on the spatial distribution of the YRB’s ecosystem health. The interaction between two factors is enhanced synergically. The decisive power of population density, rainfall, and potential evapotranspiration are more than 0.5, so these three are the main factors that influence the distribution of ecosystem health in the YRB. (3) The EVORSH framework is suitable for the measurement of ecosystem health in the YRB. The evaluation result is consistent with the actual situation in the YRB. A 3 km × 3 km grid is used as the basic research unit, and it can more accurately and scientifically express the spatial heterogeneity of ecosystem health in the YRB compared with the macro evaluation unit. This study can provide a scientific basis for ecological protection and high-quality development planning in the YRB. By integrating multi-dimensional data and methods, the EVORSH framework proposed in this study can quickly and scientifically assess the status of ecosystem health, identify the influencing factors of spatial heterogeneity, and could be applied in other similar watersheds.

The practice of straw returning to agricultural fields (SRF) affects crop yields and greenhouse gas (GHG) emissions. However, the responses of crop yields and GHG emissions vary significantly due to diverse climatic conditions, soil conditions, and field management practices. In this study, we conducted a meta-analysis to assess the effects of SRF on the crop yield and GHG emissions from staple crops in China. Our results indicate that the average increment in the yield of three staple crops is 13.00% with SRF. Moreover, SRF decreased the N₂O emissions compared to those without straw returning in regions with 800–1200 mm of MAP, SOC > 20 g kg^–1, 0.9–1.5 g kg^–1 TN, pHs of 6.5–7.5, and a SRF duration < 3 years, in rice cultivation systems, and with partial SRF. However, irrespective of the climatic conditions, soil properties, or field management practices, SRF increased the CO₂ emissions compared to those without straw returning. Additionally, while SRF significantly increased the CH₄ emissions in paddy fields, it had no discernible effect on the CH₄ uptake in upland fields compared to that without straw returning. These findings offer valuable insights for optimizing straw management practices and reducing GHG emissions in farmland ecosystems.