Urbanization in developing countries has intensified ecological degradation and reduced the availability of Urban Green Spaces (UGS), including in Bogor City, Indonesia, where public UGS covers only 4.26%—far below the national minimum requirement of 20%. Agroforestry is increasingly recognized as a viable strategy to enhance the ecological, economic, and social functions of limited urban green areas. This study assesses the sustainability of agroforestry practices in Bogor City’s public UGS using the Multi-Aspect Sustainability Analysis (MSA) method across five aspects: ecological, economic, social, infrastructure–technology, and legal–institutional. This study is grounded in three principal hypotheses: (i) the implementation of agroforestry exerts a positive effect on ecological, social, and infrastructural–technological sustainability; (ii) economic and legal–institutional dimensions constitute the major limiting factors affecting overall sustainability performance; and (iii) strategic improvements targeting key leverage factors can significantly enhance the composite sustainability index. Primary data were collected through field observations, interviews, and surveys, supplemented by secondary policy and spatial data. Results show an overall sustainability score of 51.84%, categorized as “sustainable”. Ecological (66.71%), social (60.71%), and infrastructural–technological (60.50%) aspects were sustainable, while economic (26.14%) and legal–institutional (45.14%) aspects were less sustainable. Key leverage factors influencing sustainability include microclimate regulation, canopy density, biodiversity, tourism management, consumer dependence on agroforestry products, product quality standardization, availability of processing industries, and the presence of management institutions and SOPs. Scenario analysis demonstrates that targeted improvements in these levers can substantially increase sustainability scores, with optimistic scenarios raising the aggregate index to 78.45%. Strengthening economic value chains, regulatory frameworks, management institutions, and data infrastructure is essential to enhance the adaptive capacity and long-term viability of urban agroforestry in Bogor City.

In this study, ten different plant leaves were collected from different urban microenvironments in the Hyderabad metropolitan area to assess their potential as bioindicators of air pollution. The collected leaf samples were analysed for surface PM accumulation, total chlorophyll concentration, carotenoid content, ascorbic acid, leaf extract pH, relative water content, and air pollution tolerance index (APTI). Out of ten plants, Ficus religiosa, which is located near the roadside, showed the highest PM accumulation with 54 µg/cm2. Tecoma stans showed the highest APTI value of 7.45 and ascorbic acid content of 10 mg/g, exhibiting greater tolerance to pollution, as well as potential for urban greening and air quality enhancement. Senegalia caesia with low APTI showed excellent carotenoid concentration of 19.42 mg/g, indicating that the plant is pollutant-sensitive, but activates antioxidant defence in response to oxidative stress. Hierarchical clustering analysis revealed a decent grouping of plant species based on biochemical profiles, validating stress tolerance patterns and PM deposition. The study highlights how pollutant deposition is linked to plant health and suggests that plants with adaptive leaf traits are more capable of tolerating polluted conditions. The findings of the study suggest that sensitive plants like Senegalia caesia, Lantana camara L., can serve as effective bioindicators and passive monitors of pollution levels and urban greening initiatives, and tolerant plants like Wodyetia bifurcata and Tecoma stans may contribute to a sustainable solution for mitigating urban air quality and supporting long-term environmental planning in polluted urban ecosystems.

Biological control of Bacillus licheniformis PR2 against Fusarium oxysporum and growth promotion of Pinus strobus L. as an urban greening strategy

From microclimate response to systemic adaptation: A temporal framework for socioecological urban greening under compound climate risks

Integrated Assessment of Environmental Sustainability and Urban Green Space Suitability using PCA-AHP with Zonal Prioritization: A Remote Sensing and GIS approach

Abstract Urban thermal discomfort is an escalating concern, particularly in arid cities undergoing rapid urbanization and climate change. Addressing this issue is essential for enhancing urban resilience and livability in vulnerable arid environments, like the Arabian Peninsula (AP). This study leverages Google Earth Engine, remote sensing datasets, and advanced thermal indices to evaluate spatiotemporal variations in urban thermal discomfort across 13 cities of the AP from 1990 to 2024. The results indicate that although many cities achieved a 20–40% increase in vegetation cover, localized land degradation persists in Abha and Sanaa (5–10%). This spatial disparity in vegetation recovery has influenced urban heat dynamics. Inland cities, including Riyadh, Madinah, and Makkah, exhibit the highest increases in Land Surface Temperature (LST), while cities at higher elevations and coastal locations benefit from natural cooling effects. Interestingly, highly urbanized areas often recorded lower Urban Heat Island (UHI) effects than peri-urban and rural areas, suggesting that dense urban morphology and materials with high thermal inertia can mitigate localized heating. The analysis of the Urban Thermal Field Variance Index (UTFVI) reveals that over 80% of urban areas experience high or extreme thermal stress; however, Doha, Muscat, and Sharjah demonstrate significant reductions through strategic urban greening and planning, as seen earlier through a few case studies in the region. This paper offers critical insights into sustainable urban planning and climate adaptation strategies to improve urban thermal comfort and livability in arid cities. Future research should integrate detailed land use assessments, seasonal and nocturnal thermal analyses, and dynamic modeling of key indices to accurately understand urban thermal dynamics.

The genus Stenamma Westwood contains 84 inconspicuous species of cryptic habits. Two species, S . westwoodii Westwood and S . debile (Foerster) are historically recorded from Ireland. Both species occur in Britain but most historical records of S . westwoodii there have been reassigned to S . debile . Confusion has persisted as to the identities of Irish Stenamma records, and both species are included in several recent publications covering the Irish ant fauna. This study re-evaluates all published Stenamma records from Ireland and corrects nomenclatural and distributional errors in prior literature. Examination of voucher specimens in the National Museum of Ireland (NMI) confirmed that only S . debile occurs here, and all historical S . westwoodii records can be reassigned to S . debile . While the species is still rare in Ireland, it is certainly more widely distributed than previously known, showing a southerly bias similar to the species??? British distribution. As with British and European populations, Irish records come from native woodland habitats, but also from coniferous forests, open scrub, limestone pavement, urban greens and roadside ditches. Phenological data indicate activity from January to October, with a peak in September that probably aligns with autumn nuptial flights.

Urban Air Mobility, including electric vertical takeoff and landing vehicles (eVTOL), offer a promising solution to alleviate road traffic congestion and enhance transportation efficiency in cities. However, to ensure its sustainability and operational safety, there is a need for the integrated optimization of eVTOLs and power systems which power these vehicles. Sensors play an important role in data acquisition for the model optimization especially for an environment with high uncertainty. Meanwhile, a quantitative assessment of the eVTOL’s safety level is essential for effective and intuitive supervision. This paper addresses the challenge of achieving both green and safe eVTOLs by proposing an integrated optimization framework. The framework minimizes the costs of eVTOLs and power system operation, and maximizes passenger capacity, by considering the energy stored in the eVTOL as a safety measure. IEEE 2668, a global standard that uses IDex to evaluate application maturity, is incorporated to assess the safety level during the optimization process. A case study for three Chinese cities showed that eVTOLs can utilize inexpensive surplus energy.

Abstract Background Street tree plantings are common in urban greening programs, and these trees provide important ecosystem services that increase as trees survive to maturity. Field-based monitoring to understand mortality rates and causes is valuable for urban forest management but very time-consuming. Methods We used street-level imagery to virtually monitor survival for 2,884 street trees over several years postplanting in Philadelphia, Pennsylvania, United States. Results We observed similar mortality rates to other studies, with 7.5% of trees dead or removed by the first summer after planting and the mortality rate dropping to 3.5% between the third and fourth summers postplanting. Logistic regression models were constructed over various time horizons to understand which site, neighborhood, and species characteristics related to survival outcomes. These models showed that higher tree survival was associated with less impervious surface surrounding the tree; lower social vulnerability in the neighborhood; and tree planting in the fall season as opposed to spring. Conclusions Our results point to management activities that could improve survival outcomes, such as planting site enhancements and establishment maintenance, as well as the use of monitoring data to drive decisions regarding planting season. This study demonstrates the value of streetlevel imagery interpretations to provide mortality data on a large number of street trees planted over multiple years.

Background:Urban green environments are consistently associated with improved emotional well-being and stress regulation. However, most research focuses on large-scale green spaces, younger populations, or short-term experimental exposure, leaving limited understanding of how small-scale urban greenery supports embodied well-being among midlife and older women from socially marginalized groups.Objectives:This study examines how exposure to urban green micro-environments, particularly green walls and small vegetated elements, relates to emotional regulation and positive bodily experience among Arab women aged 50–65. By integrating quantitative measures with walking interviews, the study explores how everyday encounters with urban greenery are emotionally and bodily interpreted during midlife. Methods:The study employed a mixed-methods design. Quantitatively, participants were exposed to a green wall and a comparable built environment, with assessments of positive affect and state body appreciation. Qualitatively, walking interviews were conducted along participants’everyday routes, focusing on embodied sensations, emotional responses, and place meanings associated with green and non-green urban settings. Data were analysed using linear mixedeffects models and reflexive thematic analysis.Results:Exposure to green micro-environments was associated with higher positive affect and more positive bodily experience. Walking interviews revealed that greenery was repeatedly described as enabling bodily relaxation, ease of breathing, and emotional softening rather than joy or excitement. Green elements functioned as low-threshold resources for emotional regulation and bodily comfort, particularly salient during midlife. Conclusions: Urban green micro-environments may function as everyday restorative infrastructure supporting embodied well-being among midlife Arab women. These findings extend restorative environment theories by emphasizing partial, maintenance-oriented regulation and highlight the importance of equity-oriented green design in urban neighbourhoods.

<p><strong><span lang="EN-US" style="font-size: 10.0pt; mso-bidi-font-size: 11.0pt; line-height: 115%; font-family: 'Times New Roman',serif; mso-fareast-font-family: 宋体; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;">Background:</span></strong><span lang="EN-US" style="font-size: 10.0pt; mso-bidi-font-size: 11.0pt; line-height: 115%; font-family: 'Times New Roman',serif; mso-fareast-font-family: 宋体; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;"> Air pollution significantly impacts global health, contributing to approximately 3.7 million premature deaths annually. Ahvaz, as one of the most polluted cities in the world, experiences severe air pollution due to urbanization, industrial expansion, and transportation. This study aims to identify pollution sources, evaluate their impact through a hybrid SWOT-AHP analysis, and propose innovative air quality management strategies based on global best practices. <strong>Methods:</strong> A combination of emission inventory analysis, geographic information system (GIS) mapping, and a multi-criteria decision-making (MCDM) approach was applied to assess key pollution sources. SWOT analysis was integrated with the Analytical Hierarchy Process (AHP) to prioritize effective interventions for air quality improvement. Comparative analysis was conducted with cities such as Beijing, New Delhi, and Los Angeles to benchmark pollution control measures. <strong>Results:</strong> Nitrogen oxides (NOx) were identified as the most emitted pollutants in central Ahvaz, reaching 392 tons annually. Other major pollutants included carbon monoxide (CO) (89 tons/year), suspended particles (87 tons/year), and hydrocarbons (34 tons/year). The Ramin Power Plant accounted for 54% of SO2 emissions, while oil industries contributed to 82% of total pollutants. The hybrid SWOT-AHP analysis ranked “Implementing an advanced air pollution monitoring system and smart traffic management” as the most effective strategy. Benchmarking with other global cities revealed that implementing low-emission zones and transitioning to cleaner fuels significantly reduced air pollution levels. The AHP analysis prioritized strategies as Smart Monitoring System (46.7%)</span><span lang="RU" style="font-size: 11.0pt; line-height: 115%; font-family: 'Times New Roman',serif; mso-fareast-font-family: 宋体; mso-ansi-language: RU; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;">—</span><span lang="EN-US" style="font-size: 10.0pt; mso-bidi-font-size: 11.0pt; line-height: 115%; font-family: 'Times New Roman',serif; mso-fareast-font-family: 宋体; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;">The most effective approach, emphasizing real-time pollution tracking and traffic optimization. Next Clean Fuel Transition (27.7%)</span><span lang="RU" style="font-size: 11.0pt; line-height: 115%; font-family: 'Times New Roman',serif; mso-fareast-font-family: 宋体; mso-ansi-language: RU; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;">—</span><span lang="EN-US" style="font-size: 10.0pt; mso-bidi-font-size: 11.0pt; line-height: 115%; font-family: 'Times New Roman',serif; mso-fareast-font-family: 宋体; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;">Reducing emissions by shifting industries and vehicles to low-emission fuels. Low-Emission Zones (16.0%)</span><span lang="RU" style="font-size: 11.0pt; line-height: 115%; font-family: 'Times New Roman',serif; mso-fareast-font-family: 宋体; mso-ansi-language: RU; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;">—</span><span lang="EN-US" style="font-size: 10.0pt; mso-bidi-font-size: 11.0pt; line-height: 115%; font-family: 'Times New Roman',serif; mso-fareast-font-family: 宋体; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;">Establishing restricted zones to control vehicular pollution. And Urban Green Infrastructure (9.5%)</span><span lang="RU" style="font-size: 11.0pt; line-height: 115%; font-family: 'Times New Roman',serif; mso-fareast-font-family: 宋体; mso-ansi-language: RU; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;">—</span><span lang="EN-US" style="font-size: 10.0pt; mso-bidi-font-size: 11.0pt; line-height: 115%; font-family: 'Times New Roman',serif; mso-fareast-font-family: 宋体; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;">Expanding green spaces to enhance air quality. <strong>Conclusion:</strong> Strategic investments in pollution control technologies, combined with policy interventions such as emissions-based congestion pricing and green infrastructure expansion, are crucial for mitigating pollution in Ahvaz. The SWOT-AHP framework provided a structured approach to prioritizing actionable environmental management strategies based on feasibility and effectiveness.</span></p>

Green innovation efficiency (GIE) serves as a key indicator of urban development toward “dual carbon” goals and sustainable growth. However, systematic evidence remains scarce regarding the impact of the digital-real economy integration (DRI) in urban green innovation efficiency (UGIE). Based on the dual institutional perspectives of government environmental regulation (ER) and intellectual property protection (IPP), this paper proposes an integrated theoretical framework that incorporates integration level, institutional environment, and green innovation. Leveraging panel data from 281 prefecture-level and higher-administered cities in China spanning 2013 to 2023, this paper explores the underlying mechanism and the observed threshold effect of DRI on UGIE. The primary findings are summarized below: (1) DRI promotes UGIE, which is mediated significantly through the institutional roles of ER and IPP. (2) The influence of DRI on GIE is characterized by a threshold effect at a value of 0.9657. Beyond this threshold, the marginal effect rises from 0.47463 to 0.52555, thereby providing evidence for the positive feedback hypothesis between integration level and institutional response. (3) A more significant effect of DRI on GIE could be observed in non-resource-based cities, such as the central cities, southern cities and eastern cities. This paper expands the interdisciplinary research on digital economy and urban sustainability, providing micro-level evidence for the tailored development of digital–green institutional combinations.

The ecological benefits of urban green spaces depend on their structure and ecological service function. Evaluation systems used to monitor these characteristics show distinct regional variations. This study analyzed China’s urban green spaces, developed a quantitative ecological benefit evaluation system, and comprehensively evaluated the ecological benefits of green spaces in Xi’an city. Suitable evaluation indexes for Xi’an were selected based on field survey data with large-scale samples and high-resolution remote sensing image data. The results showed that the ecological service function of urban green spaces in Xi’an has been substantially improved by ecological planning. Therefore, it is important to evaluate this function as part of the urban planning and design process. Furthermore, increasing the 3D Green Quantity through urban forests can effectively improve the ecological service function.

Urban Heat Island (UHI) effects are exacerbated by the expansion of impervious surfaces and loss of vegetation in urban centers, leading to elevated air and surface temperatures and reduced thermal comfort. Urban trees, through shading and evapotranspiration, are among the most effective Nature-based Solutions (NbS) for passive cooling. This study assesses the cooling potential of selected tree species by analyzing their morphological and physiological traits using a combination of ENVI-met microclimate simulations and multiple regression modeling. A total of 15 urban tree species were selected from the literature and analyzed based on their dependency of their cooling efficacy. Later validated in urban setting by Envi-met simulations. Key traits, such as Leaf Area Index (LAI), canopy density, transpiration rate, tree height, rooting depth, and water availability, were analyzed. Multiple linear regression analysis was conducted to quantify the contribution of each trait to ambient temperature reduction. Results revealed that LAI (R² = 0.76, p < 0.001) and transpiration rate (R² = 0.71, p < 0.001) were the most significant predictors of daytime cooling, while canopy openness and tree height were more strongly correlated with nighttime heat dissipation. High-performing species, such as Ficus benghalensis, Azadirachta indica, and Samanea saman, demonstrated a maximum temperature reduction of 2.5–4.2 °C, especially in compact, low-rise, and mid-rise zones. The study provides a quantitative trait-based framework for tree selection in urban greening initiatives and offers evidence to guide landscape planning and UHI mitigation strategies through scientifically informed plantation design.

Street greenery, as critical green infrastructure, provides extensive ecosystem services, and accurately evaluating its value benefits urban greening strategies and funding decisions. Previous studies relying on cross-sectional data and hedonic regression models are limited by confounding factors, thus failing to accurately measure the net effects of street greenery characteristics on housing prices. To address this limitation, hedonic regression, propensity score matching and difference-in-differences methodologies were employed based on housing price and built environment data from 2017 to 2022 to analyze how street greenery quantity and vegetation structure affect housing prices. Results indicated that street greenery impacts differ significantly between the central area and the expanded central area, revealing a negative price effect defined as the “Green Burden Effect” in expanded central area. Additionally, greenery quantity changes exerted stronger and more stable price impacts compared to vegetation structure. The DID analysis further clarified temporal changes in these relationships. Employing multiple econometric models revealed the complex spatial-temporal relationships between street greenery and housing prices, emphasizing the importance of spatially targeted greening strategies to optimize residential values and promote equitable urban development.

The rapid expansion of urban areas has intensified the Urban Heat Island (UHI) effect, particularly in high-density cities characterized by extensive impervious surfaces and limited green spaces. Rising surface temperatures increase energy consumption, reduce outdoor thermal comfort, and pose serious public health risks during extreme heat events. Urban greening is widely recognized as an effective heat mitigation strategy; however, in densely built environments, indiscriminate or uniform distribution of green spaces often fails to achieve optimal cooling benefits. This study proposes an artificial intelligence–based framework for strategically optimizing urban green space placement to maximize heat reduction while accounting for land-use constraints. The proposed approach integrates multisource remote sensing data, vegetation indices, land surface temperature measurements, and urban morphological indicators with machine learning–based thermal modeling. A Random Forest Regression model is employed to capture the nonlinear relationships between vegetation cover, built-up density, and surface temperature, followed by a spatial optimization process to identify priority locations for greening interventions. Experimental results demonstrate a strong negative relationship between vegetation density and land surface temperature, with optimized greening scenarios achieving temperature reductions of up to 2.6°C, significantly outperforming uniform greening strategies with equivalent green area allocation. The findings highlight that the spatial configuration and targeted placement of green spaces are more influential than total green cover alone. By incorporating explainable AI techniques, the framework also provides interpretable insights into the dominant drivers of urban heat, enhancing transparency for planning applications. Overall, this study offers a data-driven and decision-oriented methodology that can support urban planners and policymakers in designing effective, climate-resilient strategies for mitigating heat stress in high-density urban environments.

Against the escalating challenges of global climate change and intensifying resource-environment constraints, exploring the green effects of industrial spatial organization has become crucial. Utilizing panel data from the Yangtze River Delta cities spanning 2011–2023, this study empirically examines the nonlinear impact of manufacturing-producer services co-agglomeration on urban green efficiency. The results reveal a significant U-shaped relationship: co-agglomeration initially suppresses efficiency due to coordination costs and congestion effects, but after crossing a specific threshold, the resulting scale economies and knowledge spillovers dominate and begin to promote green enhancement. Mechanism tests indicate that industrial upgrading serves as a direct mediating channel, while the mediating effect of green technological innovation exhibits a time lag. Further heterogeneity analysis shows that this U-shaped pattern is particularly pronounced in cities with low agglomeration levels, those not designated as low-carbon pilots, and non-resource-based cities. This study uncovers the nonlinear dynamics and key boundary conditions of the green effects arising from industrial co-agglomeration, providing an empirical basis for implementing differentiated regional spatial coordination policies.

This study investigates the effects of saline reclaimed water recharge on soil salt accumulation and water migration in Xinjiang, China, aiming to provide scientific guidance for the sustainable utilization of reclaimed water in arid regions. Indoor vertical infiltration simulation experiments were conducted using reclaimed water with varying salinity levels (0, 1, 2, 3, and 4 g L−1) to evaluate their impacts on soil water–salt distribution and infiltration dynamics. Results showed that irrigation with saline reclaimed water increased soil pH and significantly enhanced both the infiltration rate and wetting front migration velocity, while causing only minor changes in the moisture content of the wetted zone. When the salinity was 2 g L−1, the observed improvement effect was the most significant. Specifically, the cumulative infiltration increased by 22.73% after 180 min, and the time required for the wetting peak to reach the specified depth was shortened by 21.74%. At this salinity level, the soil’s effective water storage capacity reached 168.19 mm, with an average moisture content increase of just 6.20%. Soil salinity increased with the salinity of the irrigation water, and salts accumulated at the wetting front as water moved downward, resulting in a characteristic distribution pattern of desalination in the upper layer and salt accumulation in the lower layer. Notably, reclaimed water recharge reduced soil salinity in the 0–30 cm layer, with salinity in the 0–25 cm layer decreasing below the crop salt tolerance threshold. When the salinity of the reclaimed water was ≤2 g L−1, the salt storage in the 0–30 cm layer was less than 7 kg ha−1, achieving a desalination rate exceeding 60%. Reclaimed water with a salinity of 2 g L−1 enhanced infiltration (wetting front depth increased by 27.78%) and desalination efficiency (>60%). These findings suggest it is well suited for urban greening and represents an optimal choice for the moderate reclamation of saline-alkali soils in arid environments. Overall, this study provide a reference for the water quality threshold and parameters of reclaimed water for urban greening, farmland irrigation, and saline land improvement.

In Ukraine, the digital transformation of public transport is becoming increasingly relevant, especially in the context of the implementation of the National Transport Strategy of Ukraine for the period until 2030. However, its implementation requires a comprehensive approach and coordinated decisions between the state, carriers, and the public. This study analyzes the main economic and infrastructure aspects of the digitalization of passenger transport, identifies key challenges and suggests possible ways to overcome them. The article examines the concept of Smart City as a new paradigm for the development of urban space in the context of the digital transformation of society. The essence and key components of the “smart city” model are analyzed, its impact on modern urbanism is determined, and examples of Smart City implementation in global and Ukrainian practice are given. The main challenges and prospects for the introduction of digital technologies into the urban environment are outlined. It is concluded that digitalization is an important factor in the sustainable development of cities and the formation of a comfortable living space for citizens. Modern urban development is characterized by global processes of urbanization and digital transformation. Traditional approaches to urban space management are becoming insufficient to solve complex socio-economic and environmental problems. In this context, the Smart City concept takes on the significance of a new urban paradigm that combines spatial, social, and technological aspects of urban development. The aim of the article is to study the concept of Smart City as an innovative model of urban space development and determine its role in the formation of a new urban paradigm. Among the main challenges of Smart City, we can highlight: cybersecurity and personal data protection, inequality in access to digital technologies, the high cost of implementing innovative infrastructure, the need to adapt technologies to the historically formed urban environment. The prospects for the digitalization of urban space are related to: the implementation of integrated city management platforms, the use of artificial intelligence to predict urban processes, the development of “green urbanism” in combination with digital solutions, and the active involvement of citizens in decision-making processes. The Smart City concept forms a new paradigm of urban planning, changing approaches to city management and the organization of urban space. Its implementation ensures increased management efficiency, an increase in the quality of life of residents, and creates conditions for sustainable development. Incorporating digital technologies into urban development strategies is becoming a key condition for the competitiveness of modern cities.

The rapid urbanization in China has profoundly transformed social structures, environmental conditions, and public health landscapes within a relatively brief period. While driving economic growth, it has also generated complex mental health challenges. We explored the multifaceted relationships between urbanization and mental health in China, highlighting spatial and demographic disparities, impact pathways, and intervention strategies. Mental health outcomes are shaped not by a simple urban-rural divide but by many determinants such as age, gender, chronic illness, socioeconomic status, and stage of life. Vulnerable groups, including rural older adults, migrant workers, left-behind or migrant children, and urban youth, face elevated psychological risks from environmental stressors, social exclusion and institutional barriers. Key influences are likely to involve the physical environment, social system, economic factors and policy frameworks. In addition, intervention strategies emphasize both individual and structural approaches, such as community-based psychosocial support, urban greening, inclusive policy design, and integrated mental health governance. However, current research on their impacts remains constrained by methodological limitations. This review underscores the need for equity-oriented approaches, interdisciplinary research and policy innovations to support community mental health within China's urbanization trajectory. Aligning public mental health strategies with national initiatives like "Healthy China 2030" and dual carbon goals is imperative to building inclusive and healthy urban environments for population mental well being and resilience.