Search Results (3,729)

The linkage between land tenure security and land quality improvement investment is crucial given that the land tenure security system is a widely applied policy tool for the protection of cultivation land in developing countries. Drawing on the triple land tenure security framework, this paper examines the impact of the de jure and the de facto land tenure security on farming households’ decisions about using organic fertilizer on their plots in China, based on a national survey dataset covering 2308 plots matched with 962 farming households across 8 provinces in China (Shangdong, Shangxi, Jilin, Zhejiang, Henan, Gansu, Hunan, and Sichuan) from January to July 2013. The empirical results show that the de facto land tenure security affected the use of organic fertilizer by the farming households positively. In comparison, the impact of the de jure land tenure security on the use of organic fertilizer by farming households was modest. It is suggested that the government should implement the policies effectively to promote de jure land tenure security and encourage farming households to make sustainable land investment. Full article

Cropland is a critical component of food security. Under the multiple contexts of climate change, urbanization, and industrialization, China’s cropland faces unprecedented challenges. Understanding the spatiotemporal dynamics of cropland non-agriculturalization (CLNA) and quantifying the contributions of its driving factors are vital for effective cropland management and the optimal allocation of land resources. This study investigated the spatiotemporal dynamics and driving mechanisms of CLNA in Shaanxi Province (SP), a major grain-producing region in China, from 2001 to 2020, using geospatial statistical analysis and machine learning techniques. The results showed that, between 2001 and 2020, approximately 17,200.8 km² of cropland (8.4% of the total area) was converted to non-cropland, with a pronounced spatial clustering pattern. XGBoost-SHAP attribution analysis revealed that among the 15 selected driving factors, precipitation, road network density, rural population, population density, grain yield, registered population, and slope length exerted the most significant influence on CLNA in SP. Notably, the interaction effects between these factors contributed more substantially than the individual factors. These findings highlight the pronounced regional disparities in CLNA across SP, driven by a complex interplay of multiple factors, underscoring the urgent need to implement water-saving agricultural practices and optimize rural land-use planning to maintain the dynamic balance of cropland and ensure food security in the region. Full article

In order to solve the safety ambiguity problems in the construction and use of rural roads in the gully area of the Loess Plateau, this paper proposes a safety assessment method based on the normal cloud model (NCM). First, a safety assessment index system is constructed by combining the key features of road traffic safety, and the weight coefficients of each index are determined by the entropy weight method (EWM) to set the assessment criteria. Then, the cloud eigenvalue of each indicator is calculated by using the normal cloud model to clarify the degree of its affiliation to different safety levels, which fully reflects the randomness and ambiguity in the assessment process. Finally, this paper selects a typical rural road in the gully area of the Loess Plateau for example analysis. The results show that the assessment method not only reduces the subjective influence of the evaluation criteria, effectively solves the problem of indicator ambiguity, and provides a reliable scientific basis for improving road safety, but also provides lessons and references for the improvement of transportation safety in other similar areas; improves the safety and security capacity and service level of regional roads; meets the needs of the rural masses for safe and comfortable travel; enhances the people’s sense of well-being, accessibility, and sense of security; boosts rural development; and better promotes the optimization of regional and even nationwide transportation services and service quality. Full article

This study aims to explore the pivotal role of rural tourism in addressing the “three rural issues” and promoting rural revitalization. This study selects two representative villages in China that adopt different models of tourism development: Shibadong Village in Huayuan County, Hunan Province, which adopts a government-led model, and Yuanjia Village in Lixian County, Shaanxi Province, which follows a community-led model. This study evaluates the impact of rural tourism on rural revitalization using the Entropy-TOPSIS method. Utilizing the IPA (Importance–Performance Analysis) method and an independent samples t-test, a comparative analysis of the two models was conducted to reveal the differences in the effects of rural tourism in promoting rural revitalization between the different models. This study reveals that rural tourism positively impacts the revitalization of rural industries, ecology, culture, talent, and organization. However, the effects of tourism in promoting rural revitalization vary across different tourism development models. This study further suggests that the “multiple interlocking model” may be the future trend of rural tourism development as it can better integrate the resources of the government, communities, and enterprises to achieve more effective rural revitalization. This study deepens the theoretical link between rural tourism and rural revitalization, providing concrete guidance for practice, especially in strategies that drive comprehensive rural revitalization through tourism. Future research should further explore the corporate-led model and the multiple interlocking model and track the evolution of tourism development models through longitudinal comparisons to adapt to the changing needs of rural development. Full article

Heavy metal pollution has become an increasingly serious environmental issue, making the detection of heavy metals essential for safeguarding public health and the environment. This review aims to highlight the commonly used methods for detecting heavy metals (such as atomic absorption spectroscopy (AAS), atomic emission spectroscopy (AES), inductively coupled plasma–mass spectrometry (ICP-MS), square-wave anodic stripping voltammetry (SWASV), etc.), with a particular focus on electrochemical detection and electrode modification materials. Metal nanomaterials (such as titanium dioxide (TiO₂), copper oxide (CuO), ZIF-8, MXene, etc.) are emphasized as promising candidates for enhancing the performance of sensors due to their high surface area and excellent catalytic properties. However, challenges such as interference from non-target heavy metal ions and the formation of organometallic complexes with organic compounds can complicate the detection process. To address these issues, two potential solutions have been proposed: the development of advanced algorithms (such as machine learning (ML), back-propagation neural network (BPNN), support vector machines (SVM), random forests (RF), etc.) for signal processing and the use of pretreatment methods (such as Fenton oxidation (FO), ozone oxidation, and photochemical oxidation) to suppress such interferences. This paper aims to review commonly used methods for detecting heavy metals, with a particular emphasis on electrochemical techniques. It will also highlight the challenges faced in these methods, such as interference and sensitivity limitations, and propose innovative solutions, including the use of metal nanomaterials for improved sensor performance and the integration of advanced algorithms and pretreatment techniques to address interference and enhance detection accuracy. Full article

Oxalic acid is the most abundant low-molecular-weight dicarboxylic acid in the atmosphere, and it plays a crucial role in the formation of new particles and cloud condensation nuclei. However, most observational studies have focused on particulate oxalate, leaving a significant knowledge gap on oxalic acid vapor. This study investigated the concentrations and formation of oxalic acid vapor and oxalate in PM_2.5 at a rural tropical coastal island site in south China across different seasons, based on semi-continuous measurements using an Ambient Ion Monitor-Ion Chromatograph (AIM-IC) system. We replaced the default 25 μL sampling loop on the AIM-IC with a 250 μL loop, improving the ability to distinguish the signal of oxalic acid vapor from noise. The data revealed clear seasonal patterns in the dependent daytime and nighttime formation of oxalic acid vapor, benefiting from high signal-to-noise ratios. Specifically, concentrations were 0.059 ± 0.15 μg m⁻³ in February and April 2023, exhibiting consistent diurnal variations similar to those of O₃, likely driven by photochemical reactions. These values decreased to 0.021 ± 0.07 μg m⁻³ in November and December 2023, with higher nighttime concentrations likely related to dark chemistry processes, amplified by accumulation due to low mixing layer height. The concentrations of oxalate in PM_2.5 were comparable to those of oxalic acid vapor, but exhibited (3–7)-day variations, superimposed on diurnal fluctuations to varying degrees. Additionally, thermodynamic equilibrium calculations were performed on the coastal data, and independent size distributions of particulate oxalate in the upwind marine atmosphere were analyzed to support the findings. Full article

The COVID-19 pandemic placed significant strains on daily life, particularly affecting vulnerable groups such as rural-to-urban young migrant workers. Based on General Strain Theory (GST), these pandemic-related strains lead to delinquent copings, including excessive Internet use. However, the association between pandemic-related challenges faced by migrant youth and their digital copings has yet to be investigated. GST also posits that some conditioning factors, such as conventional beliefs, internal resilience and life satisfaction, might serve as protective factors, which can help to alleviate the disruptive consequences of the pandemic-related strains. Utilizing the fourth sweep of International Self-Report Delinquency Survey (ISRD4) in China comprising 769 working migrant adolescents aged 16 to 19, who did not attend high school, the present study examines variations in pandemic-related strains, frequent use of the Internet for gaming and social media, and their associations. In addition, this study investigates the moderating effect of three protective factors: conventional beliefs, internal resilience and life satisfaction. Results indicated that economic strain, information strain and health-related strain significantly influenced digital coping strategies, with notable gender differences. Conventional beliefs served as a significant moderator for males, while life satisfaction played a more significant moderating role for females. Relevant policy implications are then discussed. Full article

Understanding the spatial morphology and geographic adaptability of traditional settlements is crucial for their preservation and management. Accordingly, this study employs Hehuang region, China, as a case study, adopting an integrated approach that combines morphological type analysis and boundary shape index. This comprehensive methodology systematically investigates the spatial morphological features and reveals the geographic adaptability of the two types of traditional villages, which are river valley and mountain types. Specifically, the results demonstrate that: (1) The boundary morphology of river valley-type traditional villages is primarily composite, with a regular and compact overall tendency, creating a spatial pattern consisting of mountains and water bodies surrounding farmland and villages, which conveniently supports agricultural production. Their streets and alleys are mainly fishbone-shaped, dendritic, and grid-shaped. (2) Mountain-type traditional villages also exhibit composite boundary morphology but with lower compactness, higher fragmentation, and more pronounced belt-shape characteristics. Their spatial pattern facilitates agriculture and animal husbandry, with streets and alleys being predominantly grid-shaped, S-shaped, and Z-shaped. (3) The spatial morphology of both types of villages is well-adapted to local terrain and climate conditions, as well as to the resident’s requirements for water use and disaster prevention, which reflects the wisdom of the Hehuang region’s ancestors regarding settlement construction. This study contributes to comprehending the spatial characteristics and geographic adaptability of traditional villages in a multicultural area and provides a significant reference for advancing analogous traditional settlement protections and rural revitalization initiatives. Full article

This research investigates the disparities, trends and spillovers of shared prosperity for all in China during the period of 2012–2021. Taking a representative region consisting of 18 urban and rural areas as a case study, using 10 indicators such as economic development, population density and education level, along with the spatial lag model, we explore the impact of social and economic factors on common prosperity as well as the associated spillovers. Results revealed that there existed huge regional disparities in common prosperity in the short term, namely the unbalanced level of prosperity across China’s mainland, while in the long term, the common prosperity level appears to be gradually enhanced with the convergence of income ratio lines. Meanwhile, common prosperity is spatially correlated with each other, with the spatial distribution features of high–high and low–low agglomerations. Based on the model analysis, there are mixed spillovers in the evolution of common prosperity: factors like education level and population density have positive spillovers while the rest of the factors have negative spillovers. To recap, population density and education level can significantly abridge the disparities in urban and rural areas. Full article

Achieving sustainable rural development in China requires effectively integrating agricultural growth with ecological balance. However, existing research on the coordination between agricultural economy and ecosystems has often focused on isolated aspects, such as economic growth or ecological sustainability, or has been limited to specific provinces or regions, lacking a comprehensive nationwide analysis. To address this gap, this study uses spatial data from 31 provincial-level regions in China from 2008 to 2022, developing a multidimensional framework that encompasses economic input, structure, efficiency, benefits, vitality, ecological conditions, and pressure. Using multi-factor econometric methods, we comprehensively evaluate the coordination between China’s agricultural economy and ecosystems, revealing regional disparities and spatiotemporal variations in their coupling coordination, and analyzing the barriers affecting this coordination. Our findings show that: First, coupling coordination has steadily improved, narrowing regional disparities. Second, regional differences are primarily driven by variations between the eastern, central, and western regions, with structural disparities shifting from interregional to hyper-variable density. Third, development exhibits a “club convergence” pattern, where upward transitions are difficult and downward mobility is a risk. Key barriers include farmland scale, land efficiency, afforestation area, and soil erosion control. Based on these findings, we recommend regional development strategies, dynamic monitoring mechanisms, optimized land use, and enhanced ecological protection. This study provides valuable insights for policymakers and practitioners to promote the coordinated and sustainable development of agricultural economies and ecosystems in China. Full article

Background: While current epidemiological studies have documented associations between environmental metals and renal dysfunction, the majority have concentrated on plasma metal levels. The relationship between urinary metal exposure and chronic kidney disease (CKD) remains contentious, particularly within specific demographic groups. Methods: This cross-sectional study included 2919 rural Chinese adults recruited between 2018 and 2019. Urine metals were measured by ICP-MS. Least absolute shrinkage and selection operator (LASSO) regression was employed to identify metals significantly associated with CKD. Then, we used binary logistic regression, along with restricted cubic spline (RCS) models, to assess the individual exposure effects of specific metals on CKD. Quantile g-computation, weighted quantile sum regression, and Bayesian kernel machine regression (BKMR) models were applied to evaluate combined effects of metal exposures on CKD. Gender-stratified analyses were also conducted to explore these associations. Results: LASSO identified seven metals (V, Cu, Rb, Sr, Ba, W, Pb) with significant impacts on CKD. In single-metal models, Cu and W exhibited a positive correlation with CKD, whereas V, Rb, Sr, Ba, and Pb showed significant negative correlations (all p < 0.05). RCS analysis revealed nonlinear associations between V, Cu, Ba, Pb, and CKD (all p-nonlinear < 0.05). In the multi-metal model, quantile-based g-computation demonstrated a collective negative association with CKD risk for the seven mixed urinary metal exposures (OR (95% CI) = −0.430 (−0.656, −0.204); p < 0.001), with V, Rb, Sr, Ba, and Pb contributing to this effect. The WQS model analysis further confirmed this joint negative association (OR (95% CI): −0.885 (−1.083, −0.899); p < 0.001), with V as the main contributor. BKMR model analysis indicated an overall negative impact of the metal mixture on CKD risk. Interactions may exist between V and Cu, as well as Cu and Sr and Pb. The female subgroup in the BKMR model demonstrated consistency with the overall association. Conclusions: Our study findings demonstrate a negative association between the urinary metal mixture and CKD risk, particularly notable in females. Joint exposure to multiple urinary metals may involve synergistic or antagonistic interactions influencing renal function. Further research is needed to validate these observations and elucidate underlying mechanisms. Full article

Urban renewal is a critical approach to address issues such as the scarcity of urban spatial resources and infrastructure aging in the later stages of urbanization. Urban village renewal is one of the typical practices of urban renewal. Based on China’s unique dual urban–rural land system and urbanization process, this study localizes the rent gap theory. It applies the modified rent gap theory to conduct a case study on Wangjiapeng Village in Xi’an using the process-tracing method. It explores the internal mechanisms of urban village renewal and the key factors influencing the progress of renewal projects. The findings reveal that the size of the rent gap directly determines the attractiveness and timing of urban village renewal. However, issues such as interest conflicts, administrative redundancy, and government supervision during the renewal process significantly increase transaction costs, raising the rent gap threshold and thereby affecting the progress and outcomes of the renewal. This paper proposes a rent gap theory that is more suited to China’s context and further expands its applicability through case study research. The practical experience of Wangjiapeng Village provides important policy implications for other major cities in China and cities currently in the late stages of urbanization. Full article

The formation and development of new quality productivity of agriculture can effectively promote agricultural sustainability and modernization. In order to explore the multiple paths of the formation of new quality productivity of agriculture, using the panel data of 30 provincial levels in China from 2012 to 2021, based on the “technology-organization-environment” framework and dynamic QCA method, this paper explores how seven factors such as agricultural technology innovation, digital infrastructure, innovation policy support, the formation of e-commerce industry, marketization level, green finance, and rural culture modernization interact to promote the formation of new quality productivity of agriculture. The findings reveal that none of the above seven factors can promote the formation of new quality productivity of agriculture, and agricultural technological innovation and digital infrastructure are becoming more and more important to the formation of new quality productivity of agriculture over time. The high new quality productivity of agriculture formation models can be categorized into four types: TOE empowers new business model development-driven, government–market–culture triple-driven, market-oriented efficient transformation of technological achievements-driven, and deep integration of agricultural technological innovation and emerging agricultural business models-driven. The configurational results exhibit significant regional effects, with diverse pathways for the formation of new quality productivity of agriculture across different provinces. Full article

Capital plays a crucial role in driving rural sustainable development. Some rural areas have achieved revitalization through capital intervention, while others have experienced failure. It is possible that the purposes of capital intervention initiated by different parties (such as government, enterprises, and individual investors) in rural areas differ, which leads to the divergence of development routes and effectiveness. Yet, the questions of why and how this phenomenon occurs have not been well studied. Based on observation and an in-depth interview conducted in two suburban villages near Wuhan, we have established an analytical framework with which to compare the route and effectiveness of rural developments driven by capital intervention. The results are as follows: (1) The sources of capital and the embedded purposes determine the modes of rural resource reconfiguration and the arrangement of the relevant industrial sectors. The answer to the question of how to allocate capital gains among different interest groups engaged in rural development determines whether a community of shared interests with respect to sustainable rural development can be established and operate effectively. (2) As the profit-making process differs among capital originating from different sources, it is necessary to evaluate this process such that the pursuit of capital gains and its influence upon rural sustainable development can be clarified and coordinated. (3) Throughout the capital intervention process, villagers’ participation is crucial as it is the prerequisite for the establishment of a mutually beneficial win–win relationship between external capital investors and local villagers. This comparative study of the two villages can provide insights into policy formulation for the purpose of rural revitalization in China and other countries in the Global South undergoing rapid urbanization. Full article

Under China’s rural revitalization strategy, peri-urban villages function as pivotal nodes in urban–rural integration. Existing policy research predominantly emphasizes macro-level land and industrial policies, neglecting their spatial development effects on peri-urban villages. This study addresses the gap by constructing a policy quantification framework and employing a Vector Autoregression (VAR) model to analyze policy impacts on rural spatial development, focusing on peri-urban villages in Dalian’s main districts from 2004 to 2023. The results indicate a fluctuating yet upward trend in policy effectiveness. Initial supply-side policies prioritized infrastructure development, whereas subsequent demand-side policies significantly enhanced living conditions, underscoring the necessity of adaptive policy strategies. The rural revitalization construction index exhibited notable spatial heterogeneity, evolving from clusters near industrial zones to expansion into areas like the Jinzhou District, aligned with urban growth patterns. Granger causality analysis confirmed the strong influence of policy interventions, with the first-order lag VAR model offering reliable predictions of short- and long-term policy effects. Initially, the construction index was entirely self-driven (100%), but its reliance on self-influence waned to 69.8% over time, highlighting a transition toward greater policy-driven development. Full article