Search Results (1,526)

For the last few decades, the use of High-Speed Trains (HSTs) has been growing rapidly in various parts of the world. Despite rapid global expansion, many HST projects fail due to demand overestimation and cost overruns. This study analyzes factors influencing HST demand in Indonesia, aiming to identify impactful determinants from user perspectives. Employing a quantitative cross-sectional approach, this research utilized questionnaires distributed to users of different modes of transportation in the Jakarta–Bandung area, including trains, buses, travel services, and private cars. Structural Equation Modeling (SEM) via Lisrel software was used to analyze the data. The results indicate that Transit-Oriented Developments (TOD) and new urban areas significantly increase HST demand by facilitating urban growth and development. Additionally, supporting infrastructure and external factors such as road accessibility, parking availability, shuttle services, and environmental integration are pivotal in shaping commuter preferences. Although factors such as safety, comfort, and reliability are important, they alone may not be adequate to persuade consumers to use high-speed trains for their travel. Full article

The rapid adoption of electric vehicles (EVs) has driven a strong need for optimizing locations of electric vehicle charging stations (EVCSs). Previous methods for locating EVCSs rely on statistical and optimization models, but these methods have limitations in capturing complex nonlinear relationships and spatial dependencies among factors influencing EVCS locations. To address this research gap and better understand the spatial impacts of urban activities on EVCS placement, this study presents a spatially aware machine learning (SAML) method that combines a multi-layer perceptron (MLP) model with a spatial loss function to optimize EVCS sites. Additionally, the method uses the Shapley additive explanation (SHAP) technique to investigate nonlinear relationships embedded in EVCS placement. Using the city of Wuhan as a case study, the SAML method reveals that parking site (PS), road density (RD), population density (PD), and commercial residential (CR) areas are key factors in determining optimal EVCS sites. The SAML model classifies these grid cells into no EVCS demand (0 EVCS), low EVCS demand (from 1 to 3 EVCSs), and high EVCS demand (4+ EVCSs) classes. The model performs well in predicting EVCS demand. Findings from ablation tests also indicate that the inclusion of spatial correlations in the model’s loss function significantly enhances the model’s performance. Additionally, results from case studies validate that the model is effective in predicting EVCSs in other metropolitan cities. Full article

The transition to smart, zero-carbon cities relies on advanced, sustainable energy solutions, with artificial intelligence (AI) playing a crucial role in optimizing renewable energy management. This study evaluates state-of-the-art AI models for solar power forecasting, emphasizing accuracy, reliability, and environmental sustainability. Using operational data from Benban Solar Park in Egypt and Sakaka Solar Power Plant in Saudi Arabia, two of the world’s largest solar installations, the research highlights the effectiveness of hybrid AI techniques. The hybrid Convolutional Neural Network–Long Short-Term Memory (CNN-LSTM) model outperformed other models, achieving a Mean Absolute Percentage Error (MAPE) of 2.04%, Root Mean Square Error (RMSE) of 184, Mean Absolute Error (MAE) of 252, and R² of 0.99 for Benban, and an MAPE of 2.00%, RMSE of 190, MAE of 255, and R² of 0.98 for Sakaka. This model excels at capturing complex spatiotemporal patterns in solar data while maintaining low computational CO₂ emissions, supporting sustainable AI practices. The findings demonstrate the potential of hybrid AI models to enhance the accuracy and sustainability of solar power forecasting, thereby contributing to efficient, resilient, and zero-carbon urban environments. This research provides valuable insights for policymakers and stakeholders aiming to advance smart energy infrastructure. Full article

Accomplishing China’s national targets of carbon peaking and carbon neutrality necessitates proactive solutions, hinging critically on fundamentally transforming rural construction models. Current construction practices in rural areas are characterized by inefficiency, high resource consumption, and reliance on imported materials. These shortcomings not only jeopardize the attainment of climate objectives, but also hinder equitable development between urban and rural regions. Using the Digital Industrial Park in Yongtai County, Fuzhou City, as a case study, this study focuses on prefabricated public buildings in regions with extreme hot–humid climate, and innovatively integrates BIM (Building Information Modeling)-driven carbon modeling with the Gaussian Two-Step Floating Catchment Area (G2SFCA) method for spatial accessibility assessment to investigate the carbon emissions and economic benefits of prefabricated buildings during the embodied stage, and analyzes the spatial accessibility of prefabricated building material suppliers in Fuzhou City and identifies associated bottlenecks, seeking pathways to promote sustainable rural revitalization. Compared with traditional cast-in-situ buildings, embodied carbon emissions of prefabricated during their materialization phase significantly reduced. This dual-perspective approach ensures that the proposed solutions possess both technical rigor and logistical feasibility. Promoting this model across rural areas sharing similar climatic conditions would advance the construction industry’s progress towards the dual carbon goals. Full article

Urban parking around the world faces similar challenges of inadequate space, pollution, and carbon emissions. Although various smart parking technologies have been tested and implemented, they primarily aim to reduce the time spent searching for parking, without considering the impact on air quality. In this study, the air quality in three urban garages was investigated with portable instruments at the entrance and exit gates and inside the garages. Garage emissions measured include CO₂, PM_2.5, PM₁₀, NO₂, and total VOCs. The results suggested that the PM_2.5 levels in these garages tend to be higher than the ambient levels. The emissions also exhibit seasonal variations, with the highest concentrations occurring in the summer, which are 20.32 µg/m³ in Campus Green, 14.25 µg/m³ in CCM, and 15.23 µg/m³ in Washington Park garages, respectively. PM_2.5 measured from these garages is strongly correlated (with an R² of 0.64) with ambient levels. CO₂ emissions are higher than ambient levels but within the indoor air quality limit. This suggests that urban garages in Cincinnati tend to enrich ambient air concentrations, which can affect garage users and garage attendants. Portable sensors are capable of long-term emission monitoring and are compatible with other technologies in smart garage development. With portable air sensors becoming increasingly accessible and affordable, there is an opportunity to integrate these devices with smart garage management systems to enhance the sustainability of parking garages. Full article

Urban wildlife conservation is emerging as a critical component of sustainable city ecosystems. Rather than simply increasing tree abundance or species richness, conservation management should focus on key species. In this research, Xishan Forest Park in Beijing was chosen as a case study. Our aim was to identify keystone taxa critical for avian foraging and nesting during the breeding season. We performed a network analysis linking bird species, their diets, and nest plants. Dietary components were detected using DNA metabarcoding conducted with avian fecal samples. Nest plants were identified via transect surveys. Two indices of the network, degree and weighted mean degree, were calculated to evaluate the importance of the dietary and nest plant species. We identified 13 bird host species from 107 fecal samples and 14 bird species from 107 nest observations. Based on the degree indices, fruit trees Morus and Prunus were detected as key food sources, exhibiting both the highest degree (degree = 9, 9) and weighted mean degree (lnwMD = 5.21, 4.63). Robinia pseudoacacia provided predominant nesting sites, with a predominant degree of 7. A few taxa, such as Styphnolobium japonicum and Rhamnus parvifolia, served dual ecological significance as both essential food sources and nesting substrates. Scrublands, as a unique habitat type, provided nesting sites and food for small-bodied birds. Therefore, targeted management interventions are recommended to sustain or enhance these keystone resource species and to maintain the multi-layered vertical vegetation structure to preserve the diverse habitats of birds. Full article

The ongoing decade of UN restoration matches with the European goal of bringing nature back into our lives, including in urban systems, and Nature Restoration Regulation. Within such a framework, this work is aimed at highlighting the ecological rationale and strategic value of an NRRP measure devoted to forest restoration in Italian Metropolitan Cities, and at assessing respective preliminary results. Therefore, the measure’s overarching goal (not to create urban parks or gardens, but activate forest recovery), geographic extent and scope (over 4000 ha and more than 4 million planted trees and shrubs across the country), plantation model (mandatory use of native species consistent with local potential vegetation, density of 1000 seedlings per ha, use of at least four tree and four shrub species in each project, with a minimum proportion of 70% for trees, certified provenance for reproductive material), and compulsory management activities (maintenance and replacement of any dead plants for at least five years), are herein shown and explained under an ecological perspective. Current implementation outcomes were thus assessed in terms of coherence and expected biodiversity benefits, especially with respect to ecological and biogeographic consistency of planted forests, representativity in relation to national and European plant diversity, biogeographic interest and conservation concern of adopted plants, and potential contribution to the EU Habitats Directive. Compliance with international strategic goals and normative rules, along with recognizable advantages of the measure and limitations to be solved, are finally discussed. In conclusion, the forestation model proposed for the Italian Metropolitan Cities proved to be fully applicable in its ecological rationale, with expected benefits in terms of biodiversity support plainly met, and even exceeded, at the current stage of implementation, especially in terms of the contribution to protected habitats. These promising preliminary results allow the model to be recognized at the international level as a good practice that may help achieve protection targets and sustainable development goals within and beyond urban systems. Full article

Rapid urbanization and demographic shifts present significant challenges to spatial justice in green space provision. Traditional static assessments have become increasingly inadequate for guiding park planning, which now requires a dynamic, future-oriented analytical approach. To address this gap, this study incorporates population dynamics into urban park planning by developing a dynamic evaluation framework for park accessibility. Building on the Gaussian-based two-step floating catchment area (Ga2SFCA) method, we propose the human-population-projection-Ga2SFCA (HPP-Ga2SFCA) model, which integrates population forecasts to assess park service efficiency under future demographic pressures. Using neighborhood-committee-level census data from 2000 to 2020 and detailed park spatial data, we identified five types of population change and forecast demographic distributions for both short- and long-term scenarios. Our findings indicate population decline in the urban core and outer suburbs, with growth concentrated in the transitional inner-suburban zones. Long-term projections suggest that 66% of communities will experience population growth, whereas short-term forecasts indicate a decline in 52%. Static models overestimate park accessibility by approximately 40%. In contrast, our dynamic model reveals that accessibility is overestimated in 71% and underestimated in 7% of the city, highlighting a potential mismatch between future population demand and current park supply. This study offers a forward-looking planning framework that enhances the responsiveness of park systems to demographic change and supports the development of more equitable, adaptive green space strategies. Full article

Dark skies, a vital natural and cultural resource, have been increasingly threatened by light pollution due to rapid urbanization, leading to ecological degradation and biodiversity loss. As a key strategy for sustainable regional development, dark sky parks (DSPs) not only preserve nocturnal environments but also enhance livability by balancing urban expansion and ecological conservation. This study develops a novel framework for evaluating DSP suitability, integrating ecological and socio-economic dimensions, including the resource base (e.g., nighttime light levels, meteorological conditions, and air quality) and development conditions (e.g., population density, transportation accessibility, and tourism infrastructure). Using the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) as a case study, we employ Delphi expert consultation, GIS spatial analysis, and multi-criteria decision-making to identify optimal DSP locations and prioritize conservation zones. Our key findings reveal the following: (1) spatial heterogeneity in suitability, with high-potential zones being concentrated in the GBA’s northeastern, central–western, and southern regions; (2) ecosystem advantages of forests, wetlands, and high-elevation areas for minimizing light pollution; (3) coastal and island regions as ideal DSP sites due to the low light interference and high ecotourism potential. By bridging environmental assessments and spatial planning, this study provides a replicable model for DSP site selection, offering policymakers actionable insights to integrate dark sky preservation into sustainable urban–regional development strategies. Our results underscore the importance of DSPs in fostering ecological resilience, nighttime tourism, and regional livability, contributing to the broader discourse on sustainable landscape planning in high-urbanization contexts. Full article

In response to the European Union’s revised Urban Wastewater Treatment Directive, which mandates enhanced monitoring and advanced treatment of micropollutants, this study was conducted. It took place within the Coastal Landscape Park (CLP), a Natura 2000 protected area in northern Poland. The focus was on the municipal wastewater treatment plant in Jastrzębia Góra, located in a region exposed to seasonal tourist pressure and discharging effluent into the Czarna Wda River. A total of 90 wastewater samples were collected during five monitoring campaigns (July, September 2021; February, May, July 2022) and analysed for 13 pharmaceuticals and personal care products (PPCPs) using ultra-high-performance liquid chromatography tandem mass spectrometry with electrospray ionisation (UHPLC-ESI-MS/MS). The monitoring included both untreated (UTWW) and treated wastewater (TWW) to assess the PPCP removal efficiency and persistence. The highest concentrations in the treated wastewater were observed for metoprolol (up to 472.9 ng/L), diclofenac (up to 3030 ng/L), trimethoprim (up to 603.6 ng/L) and carbamazepine (up to 2221 ng/L). A risk quotient (RQ) analysis identified diclofenac and LI-CBZ as priority substances for monitoring. Multivariate analyses (PCA, HCA) revealed co-occurrence patterns and seasonal trends. The results underline the need for advanced treatment solutions and targeted monitoring, especially in sensitive coastal catchments with variable micropollutant presence. Full article

The global rise in urban-related health issues poses significant challenges to public health, particularly in cities facing socio-economic crises. In Lebanon, 70% of the population is experiencing financial hardship, and healthcare costs have surged by 172%, exacerbating the strain on medical services. Given these conditions, improving the quality and accessibility of green spaces offers a promising avenue for alleviating mental health issues in urban areas. This study investigates the psychological impact of nine urban public spaces in Beirut through a comprehensive survey methodology, involving 297 participants (locals and tourists) who rated these spaces using Likert-scale measures. The findings reveal location-specific barriers, with Saanayeh Park rated highest in quality and Martyr’s Square rated lowest. The analysis identifies facility quality as the most significant factor influencing space quality, contributing 73.6% to the overall assessment, while activity factors have a lesser impact. The study further highlights a moderate positive association (Spearman’s rho = 0.30) between public space quality and mental well-being in Beirut. This study employs a hybrid methodology combining Research for Design (RfD) and Research Through Designing (RTD). Empirical data informed spatial strategies, while iterative design served as a tool for generating context-specific knowledge. Design enhancements—such as sensory plantings, shading systems, and social nodes—aim to improve well-being through better public space quality. The proposed interventions support mental health, life satisfaction, climate resilience, and urban inclusivity. The findings offer actionable insights for cities facing public health and spatial equity challenges in crisis contexts. Full article

China’s rapid urbanization has driven tremendous socioeconomic development while posing new forms of social–spatial inequalities that challenge environmental sustainability and spatial justice. This study investigates urban park-accessibility patterns across 10 s-tier provincial capital cities in China, examining how these patterns relate to housing-price dynamics to reveal diverse manifestations of social–spatial (in)justice. Using comprehensive spatial analysis grounded in distributive justice principles, we measure park accessibility through multiple metrics: distance to the nearest park, park size, and the number of parks within a 15 min walk from residential communities. Our findings reveal significant variation in park accessibility across these cities, with distinctive patterns emerging in the relationship between housing prices and park access that reflect different forms of social–spatial exclusion and inclusion. While most cities demonstrate an unbalanced spatial distribution of parks, they exhibit different forms of this disparity. Some cities show consistent park access across housing-price categories, while others display correlations between high housing prices and superior park accessibility. We argue that these divergent patterns reflect each city’s unique combination of economic development trajectory, politically strategic positioning within national urban hierarchies, and geographical constraints. Through this comparative analysis of second-tier cities, this study contributes to broader understandings of social–spatial (in)justice and urban environmental inequalities within China’s urbanization process, highlighting the need for place-specific approaches to achieving equitable access to urban amenities. Full article

With increasing urban economic development, some industrial parks and residential areas are being situated adjacent to each other, creating a potential risk of soil and groundwater contamination from the wastewater and solid waste produced by enterprises. This contamination poses a threat to the health of nearby residents. Currently, groundwater pollution prevention and control zoning in China primarily targets groundwater environmental pollution risks and does not consider the health risks associated with groundwater exposure in industry–city integration areas. Therefore, a scientific assessment of environmental risks in industry–city integration areas is essential for effectively managing groundwater pollution. This study focuses on the high frequency and rapid pace of human activities in industry–city integration areas. It combines health risk assessment and groundwater pollution simulation results with traditional groundwater pollution control classification outcomes to develop a groundwater pollution risk zoning framework specifically suited to these integrated areas. Using this framework, we systematically assessed groundwater pollution risks in a representative industry–city integration area in the middle reaches of the Yangtze River in China and delineated groundwater pollution risk zones to provide a scientific basis for local groundwater environmental management. The assessment results indicate that the total area of groundwater pollution risk control zones is 30.37 km², accounting for 19.06% of the total study area. The first-level control zone covers 5.38 km² (3.38% of the total area), while the secondary control zone spans 24.99 km² (15.68% of the total area). The first-level control zone is concentrated within industrial clusters, whereas the secondary control zone is widely distributed throughout the region. In comparison to traditional assessment methods, the zoning results derived from this study are more suitable for industry–city integration areas. This study also provides groundwater management recommendations for such areas, offering valuable insights for groundwater control in integrated industrial–residential zones. Full article

Urban areas are at the forefront in addressing global challenges such as climate change and biodiversity loss. Among the key responses are nature-based solutions, which are increasingly being integrated into policy frameworks but which require strong community engagement for their effective implementation. This paper presents the findings of surveys conducted within the Place Lab in Katowice, Poland, an initiative developed as part of an international project and used as a participatory tool for co-creating and implementing green infrastructure. The project applies both place-based and people-centred approaches to support European cities in their transition towards regenerative urbanism. Place Lab activities encourage collaboration between local authorities and residents, enhancing awareness and fostering participation in environmental initiatives. The survey data collected during the project allowed for the evaluation of changes in public attitudes and levels of engagement and for the identification of broader societal phenomena that may influence the implementation of nature-based solutions. The findings revealed, for instance, that more women were interested in supporting the project, that residents tended to be sceptical of governmental actions on climate change, and that views were divided on the trade-off between urban infrastructure such as parking and roads and the presence of green areas. Furthermore, questions of responsibility, awareness, and long-term commitment were frequently raised. Building on the survey results and the existing literature, the study proposes a set of indicators to assess the contribution of citizen participation to the adoption of nature-based solutions. While the effectiveness of nature-based solutions in mitigating climate change impacts can be assessed relatively directly, evaluating civic engagement is more complex. Nevertheless, when conducted transparently and interpreted by experts, indicator-based assessment can offer valuable insights. This study introduces a novel perspective by considering not only drivers of engagement but also the obstacles. The proposed indicators provide a foundation for evaluating community readiness and commitment to nature-based approaches and may be adapted for application in other urban settings and in future research on climate resilience strategies. Full article

This study examines the impact of vegetation structure on bird species richness and diversity across four urban parks in Chaoyang District, Beijing. Throughout the year, using the Point Count Method (PCM), a total of 68 bird species and 4279 individual observations were recorded, with surveys conducted across all four seasons to capture seasonal variations. The parks with more complex vegetation, such as those with a higher tree canopy cover of species like poplars, ginkgo, and Chinese pines, exhibited higher bird species richness. For example, Olympic Forest Park, with its dense vegetation structure, hosted 42 species, whereas parks with less diverse vegetation supported fewer species. An analysis using PERMANOVA revealed that bird communities in the four parks were significantly different from each other (F = 2.76, p = 0.04075), and every comparison between parks showed significant differences as well (p < 0.001). Variations in the arrangement and level of disturbance within different plant communities likely cause such differences. Principal component analysis (PCA) identified tree canopy cover and shrub density as key drivers of bird diversity. These findings underscore the importance of preserving urban green spaces, particularly those with a diverse range of native tree species, to conserve biodiversity and mitigate the adverse effects of urbanisation. Effective vegetation management strategies can enhance avian habitats and provide ecological and cultural benefits in urban environments. Full article