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The critical study of China’s influence on global sustainability is imperative, given its emergence as a global power. This paper examines China’s leading environmental discourse—ecological civilization—in the global context. Although ecological civilization has become a key envisioning concept in China’s domestic environmental politics and governance, the meanings of the term on the international stage have not been fully explored. This study empirically examine how ecological civilization is integrated into the Belt and Road Initiative—China’s most significant international policy under Xi. We conducted a thematic content analysis of macro-level guiding policies that cover the core content of the Belt and Road Initiative and underpin the formulation of other sectoral-specific policies. The evidence suggests that the objectives and schemes of the Belt and Road Initiative represent a distinct interpretation of ecological civilization in comparison to its domestic version, with a heavy emphasis on developmentalism, free trade, and voluntary environmentalism but remain ambiguous about ideas such as eco-socialism, state control, and human-nature harmony. A shared aspect between domestic and international discourses is the emphasis on the use of technologies as a means of addressing environmental challenges, which suggests that the Belt and Road Initiative inspires to promote Chinese eco-technologies and industries overseas.

Abstract Background China has one of the fastest paces of the growing aging population, High-level policymakers have recently recognized the aging population presents significant challenges to the Chinese healthcare system. In this context, the healthcare-seeking behaviors of the elderly population have become an essential field of study. It is necessary to understand their access to health services and to improve their quality of life, as well as to help policymakers to formulate healthcare policy. The study empirically investigates the factors influencing the elderly population’s healthcare-seeking behaviors in Shanghai, China, especially in choosing the quality of healthcare facilities to visit. Methods We designed a cross-sectional study. The data of this study were derived from the “Shanghai elderly medical demand characteristics questionnaire” in the middle of November to early December 2017. A total of 625 individuals were included in the final sample. Logistic regression was adopted to investigate the differences in healthcare-seeking behaviors between elderly people when suffer from mild illness, severe illness and follow-up treatment. Next, the differences in gender were also discussed. Results Factors affecting the healthcare-seeking behaviors of the elderly differ in mild illness and severe illness situations. For mild illness, demographic factors (gender and age) and socioeconomic factors (income and employment) play an important role in elderly healthcare choices. Female and older elderlies are more likely to choose local, lower-quality facilities, whereas those with high income and private employment are more likely to choose higher-quality facilities. For severe illness, socioeconomic factors (income and employment) are important. Furthermore, individuals with basic medical insurance are more likely to choose lower-quality facilities. Conclusion This study has shown that the affordability of public health services should be addressed. Medical policy support may be an important way to reduce the gap in access to medical services. We should pay attention to the gender differences in the elderly’s choice of medical treatment behavior, consider the differences in the needs of male and female elderly. our findings are only for elderly Chinese participants in the greater Shanghai area.

Temperature and population growth are key drivers of energy consumption. However, the relative importance of climatic and socioeconomic factors driving energy consumption at different temporal scales is not well-understood. Therefore, we developed a time-series decomposition method to attribute the relative importance of climatic (heat index and monsoon index) and socioeconomic variables to domestic energy consumption in Hong Kong from 1981–2015. The same method was used for Singapore from 2005–2015 to test the transferability of our time-series method. Population growth and GDP were the primary drivers for domestic energy consumption in Hong Kong from 1981–2015, but the heat index became the primary driver from 2005–2015 instead. The monsoon and heat indexes were the primary drivers of domestic energy consumption in Singapore from 2005–2015. Climate change will increase air temperatures by 2–5 °C for Hong Kong and Singapore by 2100. For RCP4.5 and RCP8.5 scenarios, Singapore shows a linear relationship between temperature and domestic energy consumption, whereas the relationship is non-linear in Hong Kong. Our findings highlight the importance of understanding the impact of climatic change on monsoon mechanism and heat index, which can predict future cooling demand and help achieve sustainable development goals.

Abstract There is paucity of data regarding the outcomes of hospitalized acute pulmonary embolism (PE) patients with heart failure (HF) and Coronavirus Disease 2019 (COVID‐19) infection. We utilized the 2020 National Inpatient Sample (NIS) Database in conducting a retrospective cohort study to investigate the outcomes of hospitalized acute PE patients with HF and COVID‐19, looking at its impact on in‐hospital mortality, thrombolysis, and thrombectomy utilization as well as hospital length of stay (LOS). A total of 23,413 hospitalized acute PE patients with HF were identified in our study, of which 1.26% (n = 295/23,413) had COVID‐19 infection. Utilizing a stepwise survey multivariable logistic regression model that adjusted for confounders, COVID‐19 infection among acute PE patients with HF was found to be an independent predictor of overall in‐hospital mortality (adjusted odds ratio [aOR]: 2.77; 95% confidence interval [CI], 1.15–6.67; p = 0.023) and thrombolysis utilization (aOR: 5.52; 95% CI, 2.57–11.84; p ≤ 0.001) compared to those without COVID‐19. However, there were comparable rates of thrombectomy utilization and LOS among acute PE patients with HF regardless of the COVID‐19 infection status. On subgroup analysis, patients with HF with reduced ejection fraction was found to be associated with increased risk for in‐hospital mortality (aOR: 3.89; 95% CI, 1.33–11.39; p = 0.013) and thrombectomy utilization (aOR: 4.58; 95% CI, 1.08–19.41; p = 0.042), whereas both HF subtypes were associated with increased thrombolysis utilization. COVID‐19 infection among acute PE patients with HF was associated with higher over‐all in‐hospital mortality and increased thrombolysis utilization but had comparable hospital LOS as well as thrombectomy utilization.

Background The brain-derived neurotrophic factor (BDNF) may promote development of pulmonary hypertension and right ventricular (RV) failure. However, BDNF plasma levels were decreased in patients with left ventricular (LV) failure. Therefore, we investigated BDNF plasma levels in pulmonary hypertension patients and the role of BDNF in mouse models of pulmonary hypertension and isolated RV failure. Methods BDNF plasma levels were correlated to pulmonary hypertension in two patient cohorts, including either post- and pre-capillary pulmonary hypertension patients (first cohort) or only pre-capillary pulmonary hypertension patients (second cohort). In the second cohort, RV dimensions and load-independent function were determined by imaging and pressure–volume catheter measurements, respectively. For induction of isolated RV pressure overload, heterozygous Bdnf knockout (Bdnf+/−) mice were subjected to pulmonary arterial banding (PAB). For induction of pulmonary hypertension, mice with inducible knockout of BDNF in smooth muscle cells (Bdnf/Smmhc knockout) were exposed to chronic hypoxia. Results Plasma BDNF levels were decreased in patients with pulmonary hypertension. Following adjustment for covariables, BDNF levels negatively correlated in both cohorts with central venous pressure. In the second cohort, BDNF levels additionally negatively correlated with RV dilatation. In animal models, BDNF downregulation attenuated RV dilatation in Bdnf+/−mice after PAB or hypoxic Bdnf/Smmhc knockout mice, although they developed pulmonary hypertension to a similar extent. Conclusions Similar to LV failure, circulating levels of BDNF were decreased in pulmonary hypertension patients, and low BDNF levels were associated with right heart congestion. Decreased BDNF levels did not worsen RV dilatation in animal models, and thus, may be the consequence, but not the cause of RV dilatation.

Cities are at the forefront of the global challenges of climate change. Compared to other urban problems, the complexity and uncertainty of climate change presents new governance challenges. Consequently, new modes of urban governance have emerged to address climate change, including multilevel governance (the cooperation of governmental actors positioned at different jurisdictions and governance levels); network governance (the collaboration between public and private actors in steering collective action); and experimental governance (the trial-and-error-based interventions to generate new climate solutions). This review paper compares urban climate governance in China and the West through the three analytical perspectives. The findings show that the actors involved in urban climate governance have become more diverse in China and globally, driven by new governance mechanisms that encourage the active involvement of a broad range of state and non-state actors. However, Chinese urban climate governance does exhibit distinctive characteristics under the country's unique political-economic contexts. Therefore, care must be exercised in obtaining a nuanced and contextualized understanding of urban climate governance in China. This paper concludes by offering several suggestions for future research in Chinese urban climate governance.

This study proposes a random forest algorithm to evaluate water poverty. It shows how the machine learning technique can be used to classify the degree of water poverty into five levels: very severe, severe, moderate, mild, and very mild. The strengths of the proposed random forest method include a high classification accuracy, good operational efficiency, and the ability to handle high-dimensional datasets. The success of the proposed method is empirically illustrated through a case study in Gansu, Northwest China. The analysis shows that from 2000 to 2017, the severity of water poverty in the study area declined. In 2000, most municipalities were classified as level 1 (very severe) or level 2 (severe). In 2017, level 1 water poverty disappeared, with most municipalities classified in as level 3 (moderate) and level 4 (mild). Spatially, there is a significant difference between the water poverty levels of the western, central, and eastern parts of Gansu, and the eastern part is affected by serious water poverty problems. HIGHLIGHTS This study proposes a random forest algorithm to classify the level of water poverty.; The proposed method is empirically illustrated through a case study in Gansu, Northwest China.; The strengths of the proposed method include a high classification accuracy, good operational efficiency, and the ability to handle high-dimensional datasets.;

Abstract This paper develops an integrated framework to study the socio-spatial and temporal dimensions of urban energy transitions to investigate the development and spread of solar energy technologies in urban China. A comparative analysis of three case studies of solar energy transitions in the cities of Foshan (in Guangdong), Rizhao (in Shandong), and Wuxi (in Jiangsu) demonstrates the framework’s applicability. The results map each city’s trajectory towards low carbon energy. Transitions result from dynamic interactions among central and local governments, solar manufacturers, solar installers, and residents. Alongside industrial strategies, locally-specific factors have a determining influence on the eventual outcomes.

The restoration of the livelihood of forest-based communities is an important element of forest conservation. In this study, we developed a framework of restorative justice to critically evaluate the fairness and equity of the management of non-timber forest products (NTFPs), which is often considered an important means of livelihood restoration in forest conservation. The framework, consisting of three tenets—recognitional, procedural, and distributive justice—was applied to an ethnographic study conducted in the Greater Khingan Range—a key site of forest conservation in China. The findings reveal that attempts to commercialize and use NTFPs have failed to achieve restorative justice. From the perspective of recognition justice, which concerns the different viewpoints being considered in decision-making, there is an imbalance in representation—higher-level government's preferences for certain action result in the creation of political projects, even though they are not likely to succeed, whereas local, bottom-up NTFP projects are ignored and under-supported by the government. From the procedural perspective, the lack of engagement of experts and participation of public undermines the quality of NTFP projects and the implementation of NTFP management policies. From the distribution perspective, the opportunities to gain benefits from NTFP projects are not equally distributed between state-owned forestry enterprise (SOFE) workers and non-workers. These findings show that it is important to incorporate fairness and equity issues considerations in the design and evaluation of NTFP projects, and our restorative justice framework provides an analytical basis to do so.

Understanding the dynamics of vegetation responses to climate change can provide important information for environmental management. The Qilian Mountain Nature Reserve in Northwest China, a high-altitude mountainous region that is of critical ecological importance, has been affected by drastic climate change. However, the response of vegetation to climate change in this area has not been established. This study aims to address three unanswered questions. First, what is the relative importance of temperature and precipitation change in driving regional vegetation change? Second, how does this vegetation–climate relationship manifest itself across different timescales (e.g., seasonal)? Third, what is the spatial heterogeneity of the vegetation–climate relationship? Based on MODIS data and daily meteorological data from 41 stations within and adjacent to the reserve, we used Ensemble Empirical Mode Decomposition (EEMD), Theil-Sen median trend analysis, the Mann-Kendall nonparametric test, and Pearson correlation analysis to study the evolution of temperature, precipitation, and the normalized difference vegetation index (NDVI). The key results are as follows: (1) during 1985–2019, the temperature in the reserve has increased by an average of 0.048 ℃/a, with the largest average annual increases occurring in spring (0.069 ℃) and summer (0.056 ℃); (2) during the same period, precipitation in the reserve increased by an average of 1.17 mm/a, with the largest annual increases occurring in autumn (0.669 mm) and summer (0.545 mm); (3) during 2001–2019, the NDVI increased by an average of 0.004/a; an average annual increase was experienced in all seasons, although the largest increase occurred in summer; (4) there is a statistically significant positive correlation (0.619) between the NDVI and temperature at the annual scale; (5) in contrast, the correlation between the NDVI and precipitation is weaker and not statistically significant (0.368), which indicates that temperature is the dominant factor affecting vegetation changes in the reserve; (6) there exist seasonal differences in the vegetation–climate relationship. The positive correlation between NDVI and temperature is strongest in spring whereas the positive correlation between NDVI and precipitation is strongest in summer; (7) the vegetation–climate relations demonstrate a degree of spatial heterogeneity driven by variability in climate factors and ecosystems. The value of this research is that it analyzes the response characteristics of vegetation to climate change using multiple methods and at multiple scales, providing a useful reference for understanding vegetation changes and their response to climate change in high-altitude mountain regions.

This study examined the changing trajectory and factors that influenced the health and medical expenditure of the Chinese elderly population over the past two decades. Based on the Chinese Longitudinal Healthy Longevity Survey (CLHLS) from 1998 to 2018, inferential and multiple linear regression models were constructed. The key finding is that China has experienced a decoupling of healthcare demand (HCD) and healthcare expenditure (HCE) since around 2014, when HCE began to decline despite the fact that HCD continued to rise. This is a promising sign, suggesting that the government’s health insurance policy is working. Furthermore, participating in health insurance schemes can significantly reduce the elderly’s HCD and HCE, demonstrating that health insurance can effectively affect the elderly’s decision to seek medical treatment and improve their health condition. We also found that age, region, basic old-age insurance, and care by the government and institutions were significant factors that influenced the healthcare demand and expenditure of the elderly population.

Private (out-of-pocket) healthcare expenditure (PHCE) is a complex phenomenon that is shaped by many different factors. In this paper, we analyzed the influencing factors of PHCE in China, with a specific focus on regional differences. We found that old-age dependency ratio, income, and education have significant impacts on PHCE in all regions, whereas public HCE, number of beds in medical institutions, and economic development levels have significant impacts only in some regions. The results indicate that the government should pay attention to regional inequality and implement targeted adjustments for improving the health service system. In particular, we recommend: (1) monitoring regional inequality in PHCE and other healthcare issues to unmask geographical differences in healthcare interventions; (2) adopting regional-specific policy measures—the government should divert some resources from eastern to western and central regions to increasing the support for public health undertakings and improve the quality of the local health services while providing matching medical resources by targeting the needs of the residents; (3) paying more attention to the healthcare demand of the elderly population; and (4) improving the education level of residents to improve public health and avoid high PHCE.

This study examines how rural development in China shapes new trends in population migration. Using first-hand, village-level data from Zhejiang—an economically developed province in China—we investigated the patterns and influencing factors of population migration between rural and urban areas. We conceptualized three types of migration in rural areas: rural out-migration, rural in-migration, and rural return-migration. First-hand data were collected from 347 villages. The results show that although rural out-migration remains the dominant form of migration, rural in-migration and return-migration are also common, and the latter two are positively correlated. Further, we found evidence to support the conclusion that rural economic, social, and spatial development encourages rural in-migration and return-migration but does not have a significant impact on rural out-migration. Therefore, it is foreseeable that rural in-migration and return-migration will become increasingly common in China.

Balancing the relationship between rural development and the protection of water resources is a challenging undertaking. This study develops a coupling coordination degree (CCD) model to examine the non-linear interaction between rural development and water environment in the 11 prefectures of Gansu, northwestern China. There are three key findings. First, economic development is the key driver of rural development, whereas social development has relatively little impact. For the water environment subsystem, improved water efficiency has been the key contributor, whereas environmental carrying capacity is secondary. Second, the CCD increased steadily in the studied period, which suggests that the relationship between rural development and water environment has gradually changed from antagonistic to mutually beneficial. However, this change is not occurring rapidly and in fact shows signs of slowing. Third, the complex spatial differences of the CCD are related to the level of economic and social development, the process of urban–rural integration, and regional natural conditions. The findings of this study have great significance for further quantitative analysis of the interaction and mutual feedback mechanism between the rural economy and the water environment in China and support evidence-based policymaking.

In the ten years since committing to clean energy transition, China has formulated a large number of policies and programs to achieve some very ambitious targets. This paper argues that the dearth of empirical studies concerning the implementation of these new policies and programs has created a knowledge gap between official policy documents, which are vague and lacking in specifics, and official policy outcomes, which are unreliable. In particular, the merits and limitations of flexible implementation with regard to desirable outcomes need to be debated and clarified. This paper calls for more empirical investigation in four areas as a starting point: (1) the nature and extent of flexibility in the implementation; (2) implementation strategies and their impacts; (3) factors that shape the behavior of local officials responsible for implementation; and (4) the relationship between the central-local relation and policy implementation.

The Chinese government has pursued rural land consolidation under the Building New Rural Communities (BNRC) initiative. The consolidation projects aim to address the hollowing village problem, improve the living standards of rural dwellers, and promote urban-rural integration. Rural villages with small populations and poor infrastructure are merged into a centralized rural community, and their inhabitants are resettled. The newly vacated buildings are then converted to agriculture land, which allows cities to expand under the “no net loss” land-use policy. Despite the significance of the initiative, both in terms of the scale of operation and the impacts on the affected households, there are few empirical studies that scrutinize this form of rural restructuring. Drawing on data collected via surveys and interviews, this paper examines the processes of land consolidation and its impacts on villagers. From a development-as-modernization perspective, we outline three main processes of land consolidation: village mergers and resettlement, land circulation to rural cooperatives, and rural industrial development. Overall, the effects of land consolidation on the livelihood of resettled villagers are positive. This system generally improves housing and living conditions through increased levels of off-farm employment and income, but there are a number of barriers that may hinder a villager’s ability to find different employment. Housing and neighborhood characteristics have significant effects on the life satisfaction of villagers.

With rising income and the emergence of modern shopping centers in urban China, shopping trips by private car becomes more and more common, leading to higher carbon emissions in the transport sector. Encouraging car owners to shift transport mode from private car to public transport could achieve significant emissions reductions. This study estimate carbon emissions savings by shifting from private cars to public transport for shopping trips in urban China, using Shenyang, one of the largest cities in China, as a case study. Our results show that the average carbon emissions per shopper is 426.9 g, and the carbon emissions on weekends is 13% higher than weekdays. Moreover, shoppers travelling by private car emitted five times more carbon emission than those by public transport. We also found that car ownership gradually increased as accessibility to public transport decreased, and that more car owners chose to travel by private cars than public transport in areas with limited access. This study, thus, highlights the potential for high-quality public transport to reduce the transport sector’s carbon emissions in urban China.

Current literature highlights the role of commercial centers in cities in generating shopping trips and transport carbon emissions. However, the influence of the characteristics of commercial centers on consumer travel behavior and transport carbon emissions is not well understood. This study addresses this knowledge gap by examining shopping trips to eight commercial centers in Shenyang, China, and the CO2 emissions of these trips. We found that the locations and types of commercial centers strongly influence CO2 emissions. CO2 emissions per trip to commercial centers in the suburbs of Shenyang were on average 6.94% and 26.92% higher than those to commercial centers in the urban core and the inner city, respectively. CO2 emissions induced by wholesale centers were nearly three times higher than the lowest CO2 emissions of commercial centers in the inner city. These empirical results enhance our understanding of shopping-related transport carbon emissions and highlight the importance of optimizing urban space structure, in particular, the layout of commercial centers.

While previous studies have examined China’s changing industrial energy consumption at the national level, this study argues that it is more useful, from a policy standpoint, to conduct a regional-level analysis owing to the significant regional disparity in industrialisation in the country. This study focuses particularly on Northeast China, where the implementation of the Northeast Revitalisation Strategy in 2003 has contributed to rapid reindustrialisation, which has a serious implication for industrial energy consumption. We decompose the region’s energy consumption changes into activity, structure, and intensity effects. Our results show that the intensity effect is not the only negative factor impacting industrial energy consumption during 2003–2012. The structure effect also has a negative impact on industrial energy consumption between 2005 and 2012. However, the negative impact of the two factors is weakening and not strong enough to counter the positive impact of the activity effect. This result highlights the problem of uncoordinated policy-making in Northeast China. The development strategy, which still depends highly on traditional heavy industries, is in conflict with the national strategy of energy conservation. The two conflicting objectives of industrial revitalization and energy conservation must be reconciled for sustainability in the long term. The study concludes with policy recommendations on how to achieve such reconciliation.

Abstract The objective of this study was to evaluate clinical outcomes for patients undergoing IVF treatment where an artificial intelligence (AI) platform was utilized by clinicians to help determine the optimal starting dose of FSH and timing of trigger injection. This was a prospective clinical trial with historical control arm. Four physicians from two assisted reproductive technology treatment centers in the United States participated in the study. The treatment arm included patients undergoing autologous IVF cycles between December 2022–April 2023 where the physician use AI to help select starting dose of follicle stimulating hormone (FSH) and trigger injection timing (N = 291). The control arm included historical patients treated where the same doctor did not use AI between September 2021 and September 2022. The main outcome measures were total FSH used and average number of mature metaphase II (MII) oocytes. There was a non-significant trend towards improved patient outcomes and a reduction in FSH with physician use of AI. Overall, the average number of MIIs in the treatment vs. control arm was 12.20 vs 11.24 (improvement = 0.96, p = 0.16). The average number of oocytes retrieved in the treatment vs. control arm was 16.01 vs 14.54 (improvement = 1.47, p = 0.08). The average total FSH in the treatment arm was 3671.95 IUs and the average in the control arm was 3846.29 IUs (difference = −174.35 IUs, p = 0.13). These results suggests that AI can safely assist in refining the starting dose of FSH while narrowing down the timing of the trigger injection during ovarian stimulation, benefiting the patient in optimizing the count of MII oocytes retrieved.

This paper presents a review of scholarly work on social class identities (SCI) in second and foreign language (S/FL) educational contexts. Of the 94 studies identified, 31 were annotated. Thematic analysis was employed to identify trends elucidating where, what, and how SCI has been conceptualized, theorized, and methodologically designed. Inclusion criteria focused on SCI research in S/FL contexts, while studies examining SCI outside educational settings were excluded. Results indicate a slow-growing interest in SCI and critical theory, with a Europe-Western dominance. SCI has been approached as: a fixed category based on socioeconomic status determining educational and L2 learning factors; a performed sociocultural phenomenon grounded in individuals lived experiences; a process experienced by study-abroad and migrant individuals; and as an element of colonial difference. Research gaps include SCI examination in EFL contexts and from decolonial perspectives, highlighting the need for political action to subvert social inequalities and address colonial wounds related to socioeconomic issues.

Introduction Quality sleep is essential to our health and well-being. Summertime temperatures in the bedrooms of homes in temperate climates are increasing, especially in city apartments. There is very little empirical evidence of the effect of temperature on sleep when people are sleeping in their own bedroom. The Homes Heat Health project seeks to develop a measurable definition of temperature-related sleep disturbance and the effects on health, and so produce a credible criterion for identifying overheating in new and existing homes.Methods and analysis A cohort of at least 95 people that live in London apartments and who are free of significant personal and health factors that could affect sleep are being recruited for an ongoing observational cohort study. A baseline questionnaire determines their customary sleep patterns and health. The geometrical form and thermal characteristics of their apartments is being recorded along with temperature, relative humidity and in some apartments CO2 levels, throughout one summer. Actigraphy records nightly sleep disturbance and every morning an app-based diary captures perceived sleep quality. Questionnaires following spells of hot weather capture changes in sleep pattern, sleep quality, and consequential health and well-being.Ethics and dissemination The study protocol was approved by the Loughborough University ethics committee. The participants will receive both verbal and written information explaining the purpose of the study, what is expected of them, the incentives for participating and the feedback that will be provided. The results will be reported bi-annually to a project advisory board. Presentations will be made at conferences and the methods, intermediary and final results, in academic journals. Informing government bodies, professional organisations, construction industry representatives and housing providers is of particular importance.