Introduction: The natural disasters and climate anomalies caused by increasing global carbon emissions have seriously threatened public health. To solve increasingly serious environmental pollution problems, the Chinese government has committed itself to achieving the goals of peak carbon emissions and carbon neutrality. The low-carbon patent application is an important means to achieve these goals and promote public health.Methods: This study analyzes the basic situation, spatial network, and influencing factors of low-carbon patent applications in China since 2001 at the provincial and urban agglomeration levels using social network analysis based on data from the Incopat global patent database.Results: The following findings are established. (1) From the number of low-carbon patent applications, the total number of low-carbon patent applications in China increased year by year, while the number of applications in the eastern region was larger than those in the central and western regions, but such regional differences had been decreasing. (2) At the interprovincial level, low-carbon patent applications showed a complex and multithreaded network structure. In particular, the eastern coastal provinces occupied the core position in the network. The weighted degree distribution of China's interprovincial low-carbon patent cooperation network is affected by various factors, including economic development, financial support, local scientific research level, and low-carbon awareness. (3) At the urban agglomeration level, the eastern coastal urban agglomerations showed a radial structure with the central city as the core. Urban innovation capability, economic development, low-carbon development awareness, level of technology import from overseas, and informatization level are highly correlated with the weighted degree of low-carbon cooperation networks of urban agglomerations.Discussion: This study provides ideas for the construction and governance of low-carbon technology innovation system and perspectives for theoretical research on public health and high-quality development in China.

This study investigates the spatial structure and influencing factors of the innovation network in the advanced medical equipment and device manufacturing industry in the Yangtze River Delta (YRD). This industry is crucial to public health system resilience and regional industrial upgrading. Drawing on joint patent data from the IncoPat Global Patent Database covering the period 2005–2024, the study constructs innovation networks and conducts comparative analyses from both national and regional perspectives using social network analysis and geodetector methods. The findings reveal that: (1) At the national level, the innovation network has gradually expanded but remains sparse, characterized by a “core–periphery” structure dominated by Beijing and Shanghai. Urban participation in central and western China is limited. Short-term objectives often drive industry–university–research collaborations, and collaborations in basic research among academic institutions remain insufficient. (2) In contrast, the YRD region has formed a denser, polycentric network, with Shanghai as the primary hub and Nanjing and Suzhou as key secondary centers. Local enterprises exhibit strong incentives to engage in collaborative innovation within industry–university–research frameworks. (3) Geodetector analyses indicate that economic development, technological capability, and government policy support are major drivers of network formation, while infrastructure quality plays a crucial enabling role. The relative importance of these factors varies between national and regional levels. These results provide empirical evidence to inform regional innovation strategies and targeted policy design for strengthening collaboration in the advanced medical equipment industry.

As an underdeveloped and low-income region, the development of minority regions in Northwest China is crucial. As an important part of minority regions, Ningxia Hui Autonomous Region has insufficient endogenous power for stable economic development and high risk of returning to poverty. On the whole, the Ningxia county network shows a spatial pattern of high in the north and low in the south. However, there are great differences in the centrality of different factor flow networks. The factor connections between most counties are weak, and a close innovation network has not yet been formed. There is an obvious administrative clique structure, showing a certain degree of self-enclosure. The factor flows between counties are relatively uniform and greatly affected by geographic distance. From the perspective of integrated flow, the Ningxia county network presents a distinct core-periphery circle structure. Population size and GDP are the main factors affecting the spatial network. The policy implication of this study is that Ningxia Autonomous Prefecture should coordinate the planning of the region’s economy, technology, and transportation, so as to reduce the development gap between counties by enhancing the closeness of the county spatial association network, and ultimately realize the region’s high-quality development.

Introduction: Investigating the network of firms in a specific industry helps explain industrial location and urban functions and provides guidelines for promoting industrial restructuring and high-quality development.Methods: This study develops a network model for the relationship between firms and cities based on the data of listed Specialized, Refined, Distinctive, and Innovative (SRDI) medical device manufacturing firms in China to identify the spatial distribution and influencing factors of the urban network of such firms using network analysis and GeoDetector.Results and disscusion: Three conclusions are obtained from the study. First, the urban network of listed SRDI medical device manufacturing firms exhibits a sparse structure, with the density decreasing from east to west, and the out-degree presenting significant spatial concentration. Suzhou, Shanghai, and Shenzhen are the core of the network power. The in-degree presents low spatial concentration. Clearly differentiated network functions are observed. Second, significant spatial differences are noted between high- and low-level linkage networks from the perspective of corporate governance structure. Third, economic level, labour costs, level of opening-up, talent base, and technological innovation capability have significant effects on the urban network of listed SRDI medical device manufacturing firms.

Pollution transfer across regions has become an important source of environmental health risks and spatial health inequalities, yet its underlying transfer mechanisms and structural pathways remain insufficiently understood. This study investigates the spatiotemporal evolution of pollution transfer in China’s Yangtze River Delta (YRD) from both national and local perspectives. Using off-site environmental penalty data from large-scale enterprises between 2012 and 2023, we construct pollution transfer networks and apply social network analysis and the geographical detector method to identify structural characteristics and multidimensional driving mechanisms. This study addresses three interrelated challenges: identifying pollution transfer relationships from regulatory records, disentangling multidimensional proximity mechanisms and their interaction effects, and assessing whether pollution transfer structurally reinforces environmental health inequality across cities, which are tasks that are methodologically demanding due to the hidden nature of transfer processes and the nonlinearity of proximity effects. The results reveal that the pollution transfer network in the YRD has continuously expanded, exhibiting a pronounced core–periphery structure centered on Shanghai, Hangzhou, Nanjing, and other core cities, with strong internal linkages and outward diffusion at the national scale. Pollution transfer intensity has increased over time and displays significant proximity effects. Multidimensional proximity factors jointly shape pollution transfer, with economic proximity dominating intra-regional transfers, while institutional and technological proximity play a more critical role in extra-regional transfers. Notably, public health proximity exhibits limited independent explanatory power but significantly enhances pollution transfer when interacting with economic and institutional factors, suggesting a structural linkage between pollution redistribution and environmental health inequality. Scientifically, this study advances the understanding of pollution transfer as a networked and interaction-driven process. Practically, the findings provide quantitative support for regional collaborative governance and integrated environmental and health management in the YRD.