Search Results (21,868)

Given the background of ecological fragility in western China, the northward migration of the livestock industry, and the “carbon peak” in China, it is practically significant to discuss the evolution of carbon dioxide equivalent emission intensity (CEI) in major livestock (pigs, cattle and sheep) rearing in the Shaanxi–Gansu–Ningxia (SGN) region. This discussion aims to protect the ecology of western China, achieve sustainable and healthy development of the livestock industry, and realize the national goal of “double carbon”. In this study, we utilized statistical data from 2010 to 2021 for pigs, cattle, and sheep at the municipal level in the SGN region. We applied the methodology provided by the IPCC to comprehensively measure the carbon dioxide equivalent emissions (CEs), explore spatial and temporal trends, and analyze the driving forces behind spatial variations in the intensity with the assistance of GeoDetector. The following conclusions were drawn: Firstly, the total CEs generally exhibit fluctuating and increasing patterns. Moreover, the total CEs in different cities (states) within the region show obvious variations, with a tendency to shift toward the north. Secondly, the CEI demonstrates a clear downward trend. However, the CEI in different cities (states) exhibits increasing spatial heterogeneity. Furthermore, the western part of the region is evolving toward high-value areas, while the eastern part is evolving toward low-value areas. Lastly, the results of the GeoDetector indicate that the core driving factors are the pig, cattle, and sheep rearing structure; the urban population proportion; and the per capita gross national product. In summary, the total amount of CEs demonstrates a fluctuating increase, while the intensity shows a clear downward trend. Therefore, it is recommended to reduce CEs from livestock rearing in this region by optimizing the rearing structure of pigs, cattle, and sheep, promoting low-carbon consumption, and moderately importing livestock products. Full article

This paper presents a novel machine learning methodology able to extend the results of detailed local emission inventories to larger domains where emission estimates are not available. The first part of this work consists in the development of an emission inventory of elemental carbon (EC), black carbon (BC), organic carbon (OC), and levoglucosan (LG) obtained from the detailed emission estimates available from the Project LIFE PREPAIR for the Po Basin in north Italy. The emissions of these chemical species in combination with particulate primary emissions and gaseous precursors are very important information in source apportionment and in the impact assessment of the different emission sources in air quality. To gain a better understanding of the origins of atmospheric pollution, it is possible to combine measurements with emission estimates for the particulate matter fractions known as EC, BC, OC, and LG. To identify the sources of emissions, it is usual practice to use the ratio of the measured EC, OC, TC (Total Carbon), and LG. The PREPAIR emission estimates and these new calculations are then used to train the Random Forest (RF) algorithm, considering a large array of local variables, such as taxes, the characteristics of urbanization and dwellings, the number of employees detailed for economic activities, occupation levels and land cover. The outcome of the comparison of the predictions of the machine learning implemented model (ML) with the estimates obtained for the same areas by two independent methods, local disaggregation of the national emission inventory and Copernicus Air Modelling Service (CAMS) emissions estimates, is extremely encouraging and confirms it also as a promising approach in terms of effort saving. The implemented modelling approach identifies the most important variables affecting the spatialization of different pollutants in agreement with the main emission source characteristics and is suitable for harmonization of the results of different local emission inventories with national emission reporting. Full article

This study investigates the impact of the attitudes of the elderly on the acceptance of Thailand’s high-speed rail technology according to the technology readiness index (TRI) and technology acceptance model (TAM) theories as guidelines for policies or strategies to enhance passengers’ intentions to use high-speed rail. A self-administered questionnaire was used to collect data from 3200 elderly people aged over 60 years in the surveyed areas along high-speed rail routes in Thailand, before the use of statistical analysis and multigroup structural equation modeling (SEM) to analyze variations in the participants’ attitudes toward urban and rural areas. The results that were thus obtained from both groups showed their differing attitudes toward the acceptance of technology. The TAM theory considers the attitude toward high-speed rail use in urban areas to be important, while, in rural areas, attitudes and perceived usefulness are important. With respect to the ease of use of high-speed rail, the most important factors were attitudes toward use and perceived usefulness. For the TRI theory, innovativeness features as the most positive influence on the perceived ease of high-speed rail use in both groups. Optimism and innovativeness were positive influences, but discomfort and insecurity carried a negative influence with respect to the perceived ease of use and usefulness. Full article

Managing stray cats in urban areas is an ongoing challenge, and in Australia, many are euthanized. Most stray cats are from disadvantaged areas and are under 1 year of age. The Australian Pet Welfare Foundation intended to assess the impact of a free cat sterilization program in an area with high shelter intake of cats in the city of Ipswich, Queensland. The aims of this pre-intervention study were to undertake a situational analysis of cat ownership, semi-ownership and cat caring behaviours, and compare those in the same demographic with dog ownership and caring behaviours relating to sterilization rates, to provide a basis against which to assess the program’s effectiveness. In a sample of 343 participants from that area, 35% owned cats and 3% fed stray cats. Cats were predominantly obtained from family or friends (31%) and shelters (20%). More respondents owned dogs (53%), which were most often sourced from breeders (36%) and family acquaintances (24%). More owned cats than owned dogs were sterilized (91% versus 78%). However, only 74% of cats aged 4 to <12 months were sterilized. Cat containment practices varied, with 51% of owners containing their cat(s) at all times, and a further 18% doing so at night. These results suggest the need for community-based programs that focus on sterilizing owned and semi-owned cats, and assisting semi-owners in becoming full owners to reduce stray cat populations and associated negative impacts. This includes assistance with cat containment where vulnerable native species are present. Public understanding of the causes and effective solutions for free-roaming cats, alongside legislative changes, are required to facilitate these efforts. Assistive programs aligned with One Welfare principles are expected to benefit the wellbeing of animals, humans and their environments. Full article

Prior studies have failed to adequately address intangible characteristics and lacked a comprehensive quantification of cultural dimensions. Additionally, such works have not merged supervised and unsupervised classification methodologies. To address these gaps, this study employed multidimensional numerical techniques for precise spatial pattern recognition and urban morphology classification at the block scale. By examining building density, mean floor numbers, functional compositions, and street block mixed-use intensities, alongside historical and contemporary cultural assets within blocks—with assigned weights and entropy calculations from road networks, building vectors, and POI data—a hierarchical categorization of high, medium, and low groups was established. As a consequence, cluster analysis revealed seven distinctive morphology classifications within the studied area, each with unique spatial configurations and evolutionary tendencies. Key findings include the dominance of high-density, mixed-use blocks in the urban core, the persistence of historical morphologies in certain areas, and the emergence of new, high-rise clusters in recently developed zones. The investigation further elucidated the spatial configurations and evolutionary tendencies of each morphology category. These insights lay the groundwork for forthcoming studies to devise morphology-specific management strategies, thereby advancing towards a more scientifically grounded, rational, and precision-focused approach to urban morphology governance. Full article

Urban parks are vital for mitigating high urban temperatures, yet optimizing their design for maximum cooling benefits remains a challenge. This study investigates the cooling mechanisms of 65 parks in Tianjin, assessing their characteristics and spatial equity regarding cooling capacity. Results show that 63 parks significantly lower temperatures, with an average Park Cooling Area (PCA) of 45.0 hectares, Park Cooling Efficiency (PCE) of 8.09, Park Cooling Gradient (PCG) of 16.4 °C/km, and Park Cooling Intensity (PCI) of 2.64 °C. Key factors influencing cooling effectiveness include park albedo and nearby water bodies, with optimal albedo values between 3 and 3.6, and water bodies of at least 2.5 hectares enhancing efficiency. Notably, only 38.9% of residents can easily access park cooling services. While neighborhood parks in dense urban areas provide high economic benefits, they serve fewer residents; comprehensive parks cover more people but are less accessible. This study offers new insights into the cooling effects of coastal urban parks, aiding planners in addressing marginalized residents’ needs and enhancing urban resilience amid climate change. Full article

Bus transit plays a vital role in urban public transportation but often struggles to provide accurate and reliable departure times. This leads to delays, passenger dissatisfaction, and decreased ridership, particularly in transit-dependent areas. A major challenge lies in the discrepancy between actual and scheduled bus departure times, which disrupts timetables and impacts overall operational efficiency. To address these challenges, this paper presents a neural network-based approach for real-time bus departure time prediction tailored for smart IoT public transit applications. We leverage AI-driven models to enhance the accuracy of bus schedules by preprocessing data, engineering relevant features, and implementing a fully connected neural network that utilizes historical departure data to predict departure times at subsequent stops. In our case study analyzing bus data from Boston, we observed an average deviation of nearly 4 minutes from scheduled times. However, our model, evaluated across 151 bus routes, demonstrates a significant improvement, predicting departure time deviations with an accuracy of under 80 s. This advancement not only improves the reliability of bus transit schedules but also plays a crucial role in enabling smart bus systems and IoT applications within public transit networks. By providing more accurate real-time predictions, our approach can facilitate the integration of IoT devices, such as smart bus stops and passenger information systems, that rely on precise data for optimal performance. Full article

As a novel industrial space to cope with global competition, industrial parks have gradually become important growth poles to promote regional development and provide a large number of employment opportunities. This study utilizes mobile phone signaling data to identify the commuting origins and destinations (OD) of different industrial parks in Nanjing while comparing the distribution of the working population, residential population, and commuting patterns across varying types and levels of industrial parks. The level of coordination of the employment–residential system in each park is quantified by calculating the resident commuting index (HSC_i), employee commuting index (WSC_i), and their coupling coordination degree. Additionally, geographic detectors are employed to identify the influencing factors and interaction effects that impact the employment–residential balance in industrial parks. Results show that industrial parks located in the central urban area attract more residential and working populations. The commuting volume of national and municipal as well as high-tech industrial parks is higher than other types of industrial parks. Most industrial parks experience more inward than outward commuting, and there is an uneven distribution of commuting flows, resulting in a network-like pattern of “central dense, peripheral sparse”. Various industrial parks exhibit a highly coupled job–housing system, and those with high HSC_i tend to have high WSC_i as well. The coupling coordination of industrial parks ranged from 0.16 to 0.93, with 13 being primary coordination or above and 3 being disordered. Industrial parks are classified into three types: employment-oriented, residential-oriented, and employment–residential balanced, with the residential-oriented type being predominant. The density of public transportation stops, park area, and land use mix are the primary factors affecting the employment–residential balance. Industrial parks with larger scale, better land allocation, and higher service facility levels are more likely to achieve coordination in the employment–residential system. Our work utilizes mobile signaling data to characterize the commuting patterns of industrial parks, providing insights for industrial park planning and promoting the integration of industry and city. Full article

The rapid urbanization and population growth in mega-cities have led to a significant increase in the demand for medical services, highlighting the critical need for a more efficient alignment between the supply and demand of medical resources. Previous research often focuses on singular factors, such as accessibility or quantity, as the primary criteria for matching medical services, without comprehensively considering the location, scale, and quality factors of medical facilities. Addressing this gap, this study develops a theoretical framework that integrates these three critical factors to assess the supply–demand matching (SDM) of medical care facilities (MCFs) with population needs. This assessment is conducted using geospatial analysis techniques with ArcGIS and Python. The study includes an empirical analysis of 134 streets within the Chongqing municipality. The empirical results reveal significant disparities in the performance of integrated medical care facilities (MCFs), as well as variations across the dimensions of location, scale, and quality. Central districts like Yuzhong demonstrate high levels of accessibility, appropriate scale matching, and satisfactory service quality, whereas rapidly urbanizing peripheral districts such as Yubei suffer from significant mismatches in resource availability and service quality. The theoretical framework contributes to the field of medical care research, and the corresponding empirical findings provide valuable insights for urban planners and policymakers to optimize the allocation of medical resources, improve healthcare accessibility, and enhance service quality across different urban areas. Full article

The City Region Food System (CRFS) approach has emerged in recent years as a framework for shaping urban food governance and policies that overcome the methodological cityism of approaches limited to urban territories defined by administrative boundaries. This article critically analyses the concept referring to the case study of the metropolitan city of Turin, Italy, as part of action research contributing to ongoing efforts to establish food policies. The discussion focuses on three dimensions: (1) the spatial definition of the city region; (2) the relation between the support of short and the re-assessment of long supply chains, with reference to a relational understanding of space; (3) the tensions between the CRFS as an analytical concept and a transformative framework. Results suggest that there is no linear path to define the spatial limits for a CRFS analysis and that a pragmatic approach can best serve policies; that long supply chains should not be ignored but integrated into local food policies; that there are contradictions in the transformative dimension of the CRFS literature when investigating the underlying sustainable development framework from a growth-critical perspective; and that separating the analytical more clearly from the normative dimension could make the discussion more productive. Full article

Urban forests are crucial components of cities, serving as vital ‘green lungs’ that embody urban civilization and sustainability. Despite their significance in maintaining the urban environment and ecological functions, management practices for urban forests can be unreasonable at times. This study investigated the impact of two common practices, litter removal and biochar application, on soil properties in an urban forest in Changsha city, China. The aim was to understand how these practices affect soil carbon, nutrients, and microbial activity in urban settings. The results showed that soil water content (SWC), pH, available phosphorus (AP), and soil microbial biomass carbon (SMBC) were significantly reduced in areas where litter was removed compared to areas where litter was retained. Conversely, biochar application led to a significant increase in SWC, pH, AP, and SMBC. The treatment alone had no significant effects on total nitrogen (TN), soil organic carbon (SOC), and soluble soil organic carbon (SSOC) in the examined urban forests. However, the SOC and SSOC contents significantly increased over time with biochar application. Our results demonstrated that the influences of litter removal and biochar application on soil property were attributed to the regulation of AP and SMBC in the studied urban forests. This study provides a scientific basis and reference for understanding the sustainable management of urban environments and guiding future conservation efforts in urban greening spaces. Full article

For a sustainable landscape of local economies, many researchers have emphasized the importance of field-oriented differentiation in government policies. In particular, the Paris Agreement, based on the bottom-up approach, aims to maximize the participation of all economic agents, in contrast to the top-down approach of the Tokyo Protocol. In response to these global paradigm shifts in the local landscape, local governments in Korea have made significant efforts to adapt to sustainable development during the pilot phase of emission trading scheme (ETS), during the period from 2015 to 2020. This study evaluates the performance of these local government policies in the transition to a carbon-zero economy. Using the general non-radial directional distance function (GNDDF), we found that Gyeongsang Province demonstrated enhanced environmental total factor productivity (TFP) during the pilot project, whereas the Seoul metropolitan area lagged behind due to a lack of governance. As the economic center of Korea, Seoul showed poor environmental performance because of the arbitrary elimination of green belt areas and unchecked land development, resulting in environmental degradation, a trend common in many developing countries facing climate adaptation challenges. To address these urbanization issues, this study concludes that a balanced approach combining stricter regulations with market-oriented promotional incentives is essential for optimizing the transition of local economies to a sustainable landscape. Full article

Objectives: This study sought to understand the levels of vitamin K in the mature milk of Chinese lactating mothers, thereby providing a foundation for the development of appropriate intake (AI) of vitamin K for infants aged 0–5 months. Methods: Five hundred healthy lactating mothers were selected from the mature milk bank established by the Chinese Maternal and Infant Nutrition and Health Cohort by using a simple random sample procedure. Relevant information about lactating mothers and their infants was obtained by a questionnaire survey. Vitamin K1 and vitamin K2 (MK-4 and MK-7) in mature milk were determined by liquid chromatography–tandem mass spectrometry. Results: The total concentration of vitamin K in mature milk was 4.50 (2.85–6.33) ng/mL. The concentrations of vitamin K1, vitamin K2, MK-4, and MK-7 were 2.81 (1.66–4.39) ng/mL, 1.37 (0.75–2.11) ng/mL, 1.20 (0.58–1.97) ng/mL, and 0.13 (0.08–0.19) ng/mL, respectively. The concentration of vitamin K1 was highest and the concentration of MK-7 was lowest. The concentrations of vitamin K2 and MK-4 in mature milk from the south were significantly higher than those in mature milk from the north. The total vitamin K, vitamin K2, and MK-4 concentrations in mature milk of lactating mothers residing in urban areas were higher than those in rural areas. There was a tendency for the concentration of total vitamin K and vitamin K1 to increase with the mother’s age. Moreover, the concentration of MK-4 in mature milk was highest in summer, followed by spring and winter. The levels of vitamin K1 and MK-4 in mature milk were found to be affected by lactation stage; they were highest at 91–120 days and lowest at 31–60 days. Conclusions: Based on the concentration of vitamin K in mature milk found in this study, it is recommended that the appropriate intake of VK for Chinese infants aged 0–5 months is 3.49 μg/d (2.18 μg/d for VK1 and 1.06 μg/d for VK2). Full article

Floods pose significant challenges globally, particularly in coastal regions like the Philippines, which are vulnerable to typhoons and subsequent inundations. This study focuses on Naic city in Cavite, Philippines, using Geographic Information Systems (GIS) to develop flood risk maps employing two Multi-Criteria Decision-Making (MCDM) methods including Analytical Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). These maps integrate hazard, vulnerability, and exposure assessments to identify structures most vulnerable to flooding. Weight assignments in the study are derived from a literature review and expert opinions, reflecting the Philippines’ flood-prone geography and historical data. Structural attributes, categorized on a low to very high scale, were assessed based on field survey data from 555 buildings. AHP categorized 91.3% of buildings as moderate to very high risk, whereas TOPSIS placed 68% in this category, underscoring methodological disparities in data handling and assumptions. This research enhances understanding of flood threats and offers a decision-making framework for resilient flood risk management strategies. Identifying vulnerable buildings aims to support informed urban planning and disaster preparedness in flood-prone areas, thereby mitigating potential property, infrastructure, and livelihood damage. Full article

Nature-based solutions have been promoted as an effective strategy to address climate impacts, including urban temperature reduction. In this paper, we analyze the impacts of the introduction of street trees on temperature (Universal Thermal Climate Index, UTCI) for three different dates, 2000, 2023, and 2050. A 3D model was developed in Rhinoceros software for a part of George Town, on Penang Island. Four different sections of streets were simulated after integration of the model with the Grasshopper plug-in, where a parametric system was built for temperature measurements based on simulations in the Ladybug and Honeybee plug-ins. The tree species used were selected from a pool of tree species commonly planted in urban settings in Malaysia that have low and medium sensitivity to climate impacts. The results show a maximum reduction of 7 °C between 2000 and 2050, achieved on a street with an NW–SE orientation that was planted with three rows of trees. The minimum UTCI reduction achieved was 3 °C, between 2023 and 2050, in a street with NW–SE orientation that was planted with one tree row. The two streets with a SW–NE orientation showed a 5 °C temperature reduction between 2023 and 2050. Both streets have only one row of trees but different species and sizes, with the bigger trees reducing the temperature in a slightly larger area. The results show the importance of introducing and safeguarding street trees to reduce urban temperatures in the country, potentially keeping temperatures below life-threatening levels, thereby safeguarding urban health, while also reducing costs of energy consumption. Solar orientation, the number of tree rows, and their distribution impact the outcomes. The findings provide useful guidance for climate-conscious urban planning practices in Malaysia. Full article