UNASSIGNED: As China has undergone the processes of urbanization and economic development, a large migrant population has emerged, creating new family migration trends. Family migration brings about changes in urban integration costs and benefits, affecting health investment.
UNASSIGNED: The primary objective of this research is to investigate the influence of urban integration of migrant workers\' families on their mental wellbeing, with the aim of offering policy recommendations conducive to the realization of a comprehensive public health strategy in China.
UNASSIGNED: This paper uses multi-dimensional indexes to measure family urban integration, covering economic, social and psychological dimensions, which may consider the complexity of integration. Utilizing a machine learning clustering algorithm, the research endeavors to assess the level of urban integration experienced by migrant workers and their respective families. The analysis discerns three distinct clusters denoting varying degrees of urban integration within these familial units, namely high-level, medium-level, and low-level urban integration. We applied binary logit regression models to analyze the influence of family urban integration on the mental health among migrant workers. Then we conducted a series of robustness tests.
UNASSIGNED: The results show that family urban integration decreases the probability of depressive symptoms by 14.6 percentage points. Further mechanism tests show that family economic integration enhances the psychological wellbeing of migrant workers by elevating their income status. Family social integration decreases depressive symptoms by increasing social status. Family psychological integration increases the psychological health of migrant workers by making them more satisfied with their lives. The heterogeneity test shows that family urban integration and its different dimensions have a strong impact on the depressive symptoms of women, first-generation, and less-educated groups.
UNASSIGNED: This study finds that family urban integration and its economic, social, and psychological dimensions significantly reduced the depressive symptoms of migrant workers. The results of this study lead the authors to recommend formulating a family-centered policy for migrant workers to reside in urban areas, optimizing the allocation of medical resources and public services, and improving family urban integration among migrant workers in order to avoid mental health problems in the process of urban integration.

BACKGROUND: High blood pressure (HBP) and diabetes mellitus (DM) are two of the most prevalent cardiometabolic disorders globally, especially among individuals with lower socio-economic status (SES). Studies have linked residential greenness to decreased risks of HBP and DM. However, there has been limited evidence on whether SES may modify the associations of residential greenness with HBP and DM.
METHODS: Based on a national representative cross-sectional study among 44,876 adults, we generated the normalized difference vegetation index (NDVI) at 1 km spatial resolution to characterize individuals\' residential greenness level. Administrative classification (urban/rural), nighttime light index (NLI), individual income, and educational levels were used to characterize regional urbanicity and individual SES levels.
RESULTS: We observed weaker inverse associations of NDVI with HBP and DM in rural regions compared to urban regions. For instance, along with per interquartile range (IQR, 0.26) increment in residential NDVI at 0∼5 year moving averages, the ORs of HBP were 1.04 (95%CI: 0.94, 1.15) in rural regions and 0.85 (95%CI: 0.79, 0.93) in urban regions (P = 0.003). Along with the decrease in NLI levels, there were continuously decreasing inverse associations of NDVI with DM prevalence (P for interaction <0.001). In addition, weaker inverse associations of residential NDVI with HBP and DM prevalence were found among individuals with lower income and lower education levels compared to their counterparts.
CONCLUSIONS: Lower regional urbanicity and individual SES could attenuate the associations of residential greenness with odds of HBP and DM prevalence.

Equitable and effective planning of urban park green spaces (UPGSs) is an important way to promote green and healthy urban development and improve citizens\' quality of life. However, under the background of rapid urbanization, linear large cities, with their unique spatial forms and high-density population agglomerations, have brought special challenges for the planning and management of urban public green spaces. This study takes Lanzhou, a typical representative of high-density linear large cities in China, as a case study. Based on the improvement of the traditional Gaussian Two-Step Floating Catchment Area method (G2SFCA), combined with the Gini coefficient and the Lorentz curve, the social equity and spatial equity of UPGS supply-demand in the central urban area of Lanzhou were evaluated at the city and district scales. Meanwhile, the areas with shortage of UPGS supply-demand were accurately identified as the key areas for future optimization. The results show that: (1) There are significant differences in the equity of UPGS supply-demand in the linear large Lanzhou at the social and spatial levels, and most UPGS resources are enjoyed by a few people; (2) The spatial accessibility of UPGSs has an obvious \"string of beads\" distribution Characteristics, and the areas with high accessibility are mainly concentrated along rivers; (3) The equity of UPGS supply-demand exhibits a spatial gradient effect, which is characterized by a circle distribution. From the inside to the outside, it is as follows: good supply-dense population, good supply-sparse population, supply shortage-dense population, supply shortage-sparse population. Finally, based on the concept of \"progressive micro-regeneration\" and the Location Allocation model (LA), the optimal sites for new UPGSs were determined, maximizing the equity of UPGS supply-demand. This provides a practical reference for relevant management departments to optimize park layouts in the future.

Understanding the responses of ecosystem service trade-offs and synergies in metropolitan areas to the multidimensional expansion of urban space is of great significance for the optimization of regional land spatial pattern and high-quality development. With the Guangfo Metropolitan Area as research region, we used land use data and natural ecological environment data from 2000 to 2020 to measure the expansion characteristics of urban space in the dimensions of scale, distribution, and morphology by using the landscape pattern indices. We further calculated four main ecosystem services: urban cooling, habitat quality, recreation, and water conservation by the InVEST model, quantified the trade-off and synergistic relationship of multiple ecosystem services by the coupling coordination degree model, and explored its response to multidimensional urban spatial expansion by using the multi-scale geographically weighted regression model. The results showed that urban land use scale in the Guangfo Metropolitan Area continued to increase from 2000 to 2020, with an accelerated growth rate from 2010 to 2020. The ave-rage patch area of urban land in the central area and the urban land of small patches in the northeast increased, evolving from a \"dual-center\" structure to a \"single-center\" one. The distance between urban land patches in the Guangfo Metropolitan Area was relatively small, indicating a compact distribution of urban land. The distance between newly developed urban land patches was also small, but had gradually increased in recent years. The patch shape of urban land was relatively regular and less complex, but the complexity of the newly added urban land gra-dually increased. The ecosystem service trade-offs and synergies in the Guangfo Metropolitan Area had undergone significant changes, with a decrease in synergies and an increase in trade-off, and extreme trade-offs had gradually become dominant. The response of ecosystem services synergies to changes in urban land use scale was the most intense and had spatial heterogeneity, while the response to the change of distribution and morphological characte-ristics of urban land showed periodic differences.
研究都市圈生态系统服务权衡协同关系对城镇空间扩张的响应,对区域城镇空间格局优化和高质量发展具有重要意义。本研究以广佛都市圈为研究区域,基于2000—2020年土地利用数据及自然生态环境等相关数据,选取景观格局指数测度城镇空间的规模、分布、形态维度的扩张特征,利用InVEST模型计算降温服务、生境质量、自然游憩和水源涵养4项主要生态系统服务,采用耦合协调度模型量化多元生态系统服务间的权衡协同关系,并通过多尺度地理加权回归模型探究其对城镇空间多维扩张的响应。结果表明:2000—2020年,广佛都市圈城镇用地规模持续增加,且2010—2020年间的增速加快,中心区城镇用地平均斑块面积增加和东北部小斑块的城镇用地增加,都市圈由“双中心”向“单中心”演化。广佛都市圈城镇用地斑块间距离较小,分布较为紧凑,新增城镇用地间距离较小,但近年来逐渐增大。城镇用地斑块形态整体较规整,复杂度较小,新增城镇用地的形态复杂度逐渐增加。广佛都市圈生态系统服务权衡协同关系变动较为剧烈,协同关系减少,权衡关系增加,且极度权衡关系逐渐占主导地位。广佛都市圈生态系统服务协同对城镇用地规模变化的响应最剧烈且具有空间异质性,对城镇用地分布和形态变化的响应存在阶段性差异。.

Complex geological conditions, coupled with urban expansion, resource consumption, and rapid economic development, make the ecological environment of Chongqing\'s central urban area more vulnerable. To enhance the carrying capacity of resources and the environment in this region, it is significant to scientifically assess the trend of ecological risk changes in Chongqing. The article developed an ecological risk assessment index system for Chongqing, utilizing the \"pressure-state-response\" framework. The entropy weight method (EWM) is employed to assign weights to each variable, subsequently establishing a grey weighted clustering evaluation model (GWCEM). We evaluated the ecological risks of nine central urban areas in Chongqing from 2005 to 2021 and projected the ecological risk levels and changes from 2022 to 2025. Our research indicates that the comprehensive ranking of influencing factors of ecological risk in Chongqing follows this order: response factor > pressure factor > state factor. Throughout the study period, we observed a decrease in the ecological risk values of Ba\'nan, Shapingba, Jiulongpo, Nan\'an and Yubei Districts by more than 50%. These decline rates are accelerating and regional differences in ecological risk levels are diminishing. From 2022 to 2025, except Shapingba, Jiangbei, Yuzhong, and Nan\'an District which consistently maintained a \"low-risk\" level, the ecological risk levels of all other areas continue to decrease, aligning with a \"low-risk\" classification by 2025. Based on the results of ecological risk assessment and ecological risk level prediction, corresponding recommendations are proposed for ecological environment protection and ecological risk management in the central urban area of Chongqing.

The Guangdong-Hong Kong-Macao Greater Bay Area has attracted attention for its extraordinary pace of economic development and is considered to be leading the way in China\'s transformation from a manufacturing to an innovation cluster. However, due to rapid economic expansion and rapid urbanization, the Great Bay Area still struggles with low energy efficiency and environmental degradation, which has slowed down the pace of development. Therefore, in order to alleviate energy pressure, promote the country\'s sustainable development and gain a competitive advantage in the global market, researching energy efficiency and improving energy utilization efficiency is crucial. In this study, macro-level energy efficiency indicators are constructed using energy consumption data from various cities in the Greater Bay Area for the period from 2000 to 2020, and the spatio-temporal evolution of energy efficiency is analysed. The results show that all cities in the Greater Bay Area experienced an increasing trend in energy efficiency from 2000 to 2019, with significant variation in growth rates and magnitudes between cities. Compared to the nine cities in Guangdong province, Hong Kong and Macao exhibited significantly superior energy efficiency, with Foshan recording the highest growth rate of 14%. In 2020, most cities experienced a decline in energy efficiency due to the COVID-19 pandemic, with Macao experiencing the greatest decrease at 57%. Hong Kong and Macao are both in the \"low consumption and high efficiency\" target region, while Guangzhou, Shenzhen and Zhuhai are consistently in the \"both high\" region. Changes in the industrial upgrading index correspond significantly with changes in energy efficiency trajectories, with the transition from primary to secondary and tertiary industries playing a more substantial role. There is no significant association found between the strength of environmental regulation and changes in energy efficiency. The study\'s findings indicate that the most effective way to achieve economic transformation in the majority of China\'s regions is to combine adequate environmental legislation with industrial structural adjustment.

The U-Chang-Shi (Urumqi-Changji-Shihezi) urban cluster, located at the heart of Xinjiang, boasts abundant natural resources. Over the past two decades, rapid urbanization, industrialization, and climate change have significantly threatened the region\'s ecological livability. To comprehensively, scientifically, and objectively assess the ecological livability of this area, this study leverages the Google Earth Engine (GEE) platform and multi-source remote sensing data to develop a comprehensive evaluation metric: the Remote Sensing Ecological Livability Index (RSELI). This aims to examine the changes in the ecological livability of the U-Chang-Shi urban cluster from 2000 to 2020. The findings show that despite some annual improvements, the overall trend in ecological livability is declining, indicating that the swift pace of urbanization and industrialization has placed considerable pressure on the region\'s ecological environment. Land use changes, driven by urban expansion and the growth in agricultural and industrial lands, have progressively encroached upon existing green spaces and water bodies, further deteriorating the ecological environment. Additionally, the region\'s topographical features have influenced its ecological livability; large terrain fluctuations have made soil erosion and geological disasters common. Despite the central plains\' vast rivers providing ample water resources, over exploitation and ill-conceived hydrological constructions have led to escalating water scarcity. The area near the Gurbantunggut Desert in the north, with its extremely fragile ecological environment, has long been unsuitable for habitation. This study provides a crucial scientific basis for the future development of the U-Chang-Shi urban cluster and hopes to offer theoretical support and practical guidance for the sustainable development and ecological improvement of the region.

This study investigates the impact of migrants\' skills, employment sectors, urban planning and energy sectors efficiency on carbon emissions. Utilizing the static and dynamic methods Dynamic GMM, Spatial methods on a panel dataset covering 156 nations from 2000 to 2022. Our findings reveal that heightened geopolitical risk leads to both short and long run increases in carbon emissions and the ecological footprint. The results indicate positive impact of international migration, travel services and urbanization on CO2 emissions. The results also investigate interaction effects, revealing the amplifying effect of urban population density on the association between international migration and CO2 emissions. The disaggregated analysis shows that migrants positively impact CO2 emissions in high income, Lower Income while there is complex association in upper middle-income economies. The findings provide policymakers with valuable insights for prioritizing the adoption of renewable energy, sustainable urban planning, energy efficiency measures, sustainable tourism practices, carbon pricing mechanisms, international cooperation, and sustainable economic growth strategies that are tailored to specific country contexts.

Rapid urbanization considerably alters soil environment, biodiversity, and stability of terrestrial ecosystems. Soil microbial community, a key component of global biodiversity, plays a pivotal role in ecosystem stability and is highly vulnerable to urbanization. However, effects of urbanization on the diversity, stability, and network structure of soil microbial community remain poorly understood. Herein, we investigated the diversity and stability of soil microbial communities, including bacteria, fungi, and protists, across three regions with different levels of urbanization-urban, suburb, and ecoregion-using high-throughput sequencing techniques. Our results revealed that urbanization led to a notable decrease in the alpha diversity of soil microbial community, causing a significant reduction in soil stability, as assessed by the average variation degree (AVD). The loss of stability was linked to the diminished alpha diversity of the soil fungal and protistan communities, along with weakened interactions among bacteria, fungi, and protists. Notably, the majority of keystone species identified through network analysis were classified as bacteria (Proteobacteria) and displayed a strong positive correlation with the environmental factors influencing AVD. This highlights that the variability of bacteria and the immutability of fungi and protists are important to sustain soil microbial stability. Furthermore, structural equation models indicated that protistan diversity primarily drove soil microbial stability across all regions studied. In the suburban and ecoregion areas, soil microbial stability was directly influenced by the soil properties, bacterial diversity, and keystone species, as well as indirectly affected by heavy metals. These results underscore how urbanization can reduce the stability of soil microbial community via declined diversity and network complexity, whereas the establishment of ecoregions maybe contribute to preserve the diversity and stability of soil microbial community.

Urban rivers are recognized as significant sources of methane (CH4) and carbon dioxide (CO2) emissions. Despite this, the influence of land use and urbanization on carbon emissions across rural-urban rivers at the watershed scale has been insufficiently explored. This study utilized in-situ surveys of the Liao River in northern China to investigate the spatial and temporal variations of CH4 and CO2 emissions and their relationship with urbanization and its potential controlling factors. The findings revealed that CH4 emissions peaked in fall, whereas CO2 emissions were highest in summer. The average fluxes of CH4 and CO2 at the water-gas interface were 1387.22 ± 2474.98 µmol·m-2·d-1 and 52.78 ± 54.44 mmol·m-2·d-1, respectively. Water quality parameters accounted for 80.49 % of the total variation in CH4 and CO2 concentrations and fluxes. Structural equation modeling indicated that TN, TP, DTC, and conductivity had direct effects on riverine CH4 and CO2 emissions, with standardized direct effects of 0.50 and 0.49, respectively. Nutrient input emerged as the primary driver, increasing CH4 and CO2 concentrations and fluxes, particularly in urban-adjacent river sections likely receiving higher nutrient loads. This study underscores that land use and urbanization indirectly influence riverine CH4 and CO2 emissions by modifying nutrient inputs. Effective land use management and nutrient input control are recommended strategies to mitigate riverine CH4 and CO2 emissions.