In recent years, environmental degradation and the COVID-19 pandemic have seriously affected economic development and social stability. Addressing the impact of major public health events on residents’ willingness to pay for environmental protection (WTPEP) and analyzing the drivers are necessary for improving human well-being and environmental sustainability. We designed a questionnaire to analyze the change in residents’ WTPEP before and during COVID-19 and an established ordinary least squares (OLS), spatial lag model (SLM), spatial error model (SEM), geographically weighted regression (GWR), and multiscale GWR to explore driver factors and scale effects of WTPEP based on the theory of environment Kuznets curve (EKC). The results show that (1) WTPEP is 0–20,000 yuan before COVID-19 and 0–50,000 yuan during COVID-19. Residents’ WTPEP improved during COVID-19, which indicates that residents’ demand for an ecological environment is increasing; (2) The shapes and inflection points of the relationships between income and WTPEP are spatially heterogeneous before and during COVID-19, but the northern WTPEP is larger than southern, which indicates that there is a spatial imbalance in WTPEP; (3) Environmental degradation, health, environmental quality, and education are WTPEP’s significant macro-drivers, whereas income, age, and gender are significant micro-drivers. Those factors can help policymakers better understand which factors are more suitable for macro or micro environmental policy-making and what targeted measures could be taken to solve the contradiction between the growing ecological environment demand of residents and the spatial imbalance of WTPEP in the future.

Worldwide most agroecosystems effort to increase production and yields and leads to damages of a series of non-provisioning ecosystem services (ESs). To fill in the knowledge gaps pertaining to the understanding of complex relationship between agricultural harvests and other ESs, therefore this study aims to estimate the existence of Environmental Kuznets Curve (EKC) for agricultural ESs by incorporating the spatial factors. Based on the test of the spatial autocorrelation of agricultural ESs, the estimation results of spatial model are compared with general regression to explain the spatial effect of agricultural ESs. The results show that (1) contrary to expectation, the curve of the nonlinear relationship between agricultural ESs and annual household income is an inverted U-shape, and not an upright U-shape; (2) compared to non-spatial model, the turning point of the inverted U-shaped curve for agricultural ESs under the direct effect would happen earlier and happen later under the indirect effect; (3) years of formal education, vegetation coverage of field margin and cultivated land area have significantly impact on local agricultural ESs, and local perennial crops has significantly impact on agricultural ESs of neighboring villages. Results of this study have a promising application prospect to promote sustainable development of agriculture.

Agroecosystems are complex socio-ecological systems that are managed by farmers to achieve desired outcomes, including economic income and environmental benefits contributed by ecosystem services (ES). Therefore, understanding farmers’ attitudes for ES will provide references for targeted agricultural environment management, which is critical to achieving the sustainable development of agriculture. The aim of this study is to identify the attitudes of farmers regarding ES, and to test whether and how annual household income and social demographic characteristics affect farmers’ attitudes toward ES. Using face-to-face interviews to collect data and the hypothesis of environmental Kuznets curve (EKC) to provide an analytical framework, the results reveal that, in general, the perceptions of farmers’ attitudes on ES are highly complex, caused by characteristics of the farmers. Furthermore, the inflection points of the U-shaped curves, where priorities change from increasing income to paying more attention to waste assimilation and biological pest control, are identified at 17,091 and 25,071RMB, respectively. Initiatives that aim to achieve sustainable agricultural development by strengthening ES provisions should be sensitive to farmers’perceptions. Therefore, it is necessary to strengthen farmers’ educational attainment, concentrate fragmented cultivation area and create reasonable incentives for preserving and restoring of ES and increasing farmers’ income together, which then can enhance the positive outcomes from income growth.

River basins are not merely geographical spaces but also cultural-historical ecosystems, where the spatial patterns of Intangible Cultural Heritage (ICH) profoundly reflect the long-term interaction between human and environment, as well as contemporary transformations. While international research on ICH has evolved from conceptual clarification to interdisciplinary theory-building, and spatial quantitative methods have been widely applied to cultural heritage analysis, the spatial patterns, multi-scale structures, and “natural-human” driving mechanisms of ICH in continental arid river basins—particularly in the Tarim River Basin (TRB, China’s largest inland river and a key corridor of the Silk Road)—remain underexplored. To address this gap, this study takes 313 ICH items in the TRB as the research object. It uses ArcGIS 10.8.1 to visualize their spatial distribution and employs an integrated methodology—including global Moran’s I, kernel density estimation (KDE), DBSCAN spatial clustering, and geographical detector (Geodetector)—to systematically reveal their spatial characteristics and influencing factors. The findings indicate that: (1) The distribution of ICH exhibits a multi-scale feature of “global randomness with local clustering”: spatial autocorrelation is not significant at the county level, while at the micro-geographical scale, a dendritic structure characterized by “one axis, three cores, denser in the north and sparser in the south” emerges, which is highly coupled with the river network. DBSCAN clustering further identifies a “mainstem axis–tributary node” cluster system and a relatively high proportion of peripheral “noise” heritage points. (2) Agglomeration patterns vary significantly across different ICH categories, with traditional craftsmanship showing high clustering, while traditional sports, entertainment, and acrobatics display highly fragmented distributions. (3) The study reveals and validates a ternary “Water–Tourism–Urbanization” driving framework that predominantly shapes the spatial heterogeneity of ICH: water resources constitute a fundamental ecological threshold, whereas tourism development and urbanization have emerged as more explanatory social driving forces, with widespread nonlinear enhancement interactions between natural and human factors. This research moves beyond the traditional view of river basins as static cultural “containers,” providing empirical evidence for their dynamic nature as “cultural-ecological co-evolutionary systems.” The proposed ternary framework not only offers a new perspective for understanding the spatial resilience of ICH in arid regions and the potential risks of “spectacularization” and “spatial polarization” amid rapid changes, but also provides a scientific basis for spatial governance, culture-tourism integration, and the formulation of conservation strategies for ICH at the basin scale.

Research into the resilience of the water-energy-food-ecology (WEFE) system is of great significance to ensure the safety and high quality of resources in the Yellow River Basin. To investigate WEFE system resilience and its influencing factors, this paper constructs an indicator system for WEFE system resilience based on prefecture-level city data from the Yellow River Basin spanning the years 2008 to 2021, and explores its dynamic evolution. Furthermore, this paper employs the Partial Least Squares (PLS) regression model to explore the factors influencing WEFE system resilience. It utilizes a spatial panel model to investigate the spatial spillover effects of these factors. The results indicate that WEFE system resilience in the Yellow River Basin exhibits a fluctuating upward trend. Spatially, a pattern of “low in the middle and upstream regions, high in the downstream regions” emerges. Among the driving factors, infrastructure development and the degree of innovation exhibit negative spatial spillover effects, while other factors demonstrate positive spatial spillover effects. Therefore, integrated basin management needs to be promoted by considering the systematic interlinkages of water, energy, food production and ecology and the sustainable use of resources to ensure the long-term resilience of cities. These findings provide valuable insights for policymakers to formulate more effective and coordinated resource management strategies in the Yellow River Basin, and also contributes to enriching the international literature on WEFE system research.

Energy poverty is one of the major challenges to global sustainable development, while digital development, as a significant trend of the current era, is considered a key pathway to transcend traditional energy governance frameworks. Anchored in provincial panel data spanning 30 regions across China from 2003 to 2023, this study systematically examines the impact and heterogeneity of digital development on energy poverty and further explores the underlying mechanisms and nonlinear characteristics. The findings show that digital development can significantly alleviate energy poverty, and this conclusion remains valid after addressing endogeneity issues and conducting a series of robustness tests. However, the poverty reduction effect of digital development exhibits significant regional heterogeneity: the mitigation effect in central and western regions is significantly stronger than that in eastern regions, the effect in northern regions is higher than that in southern regions, and the effect in energy-disadvantaged regions is better than that in advantageous regions. Additionally, digital development alleviates energy poverty through mediating pathways such as promoting non-agricultural employment, improving human capital levels, and driving technological innovation. Notably, digital development demonstrates threshold effects and quantile heterogeneity in relation to energy poverty, characterized by diminishing marginal returns as digital development progresses; regions with higher levels of energy poverty experience more significant poverty reduction effects from digital development. This research provides a theoretical basis for energy poverty governance under the global energy crisis and offers empirical references for other countries to achieve energy sustainability goals (SDG7) through context-specific digital transformations.