Hasil untuk "Metropolitan areas"

D. Harrison, D. Rubinfeld

L. Manzo

Christopher Marquis, Maryann Glynn

Zhang Kailin, Ma Tingting, Yi Jiajun et al.

Understanding the spatial patterns and determinants of carbon emission efficiency (CEE) is essential for advancing regional low-carbon development. While existing studies focus primarily on metropolitan cores, much less is known about peri-metropolitan regions and how core cities influence their surrounding areas. To address this gap, we assess the spatio-temporal evolution of CEE in the peri-metropolitan region of Chang-Zhu-Tan, China, and identify its key drivers. The results show that, despite an overall improvement in CEE, significant core–periphery disparities and pronounced intra-periphery heterogeneity persist. The Spatial Durbin Model, estimated with two-way fixed effects, reveals significant spatial spillovers and shows that GDP growth, population density, and core–periphery economic linkages are the primary factors shaping CEE variation. These findings provide a spatially explicit perspective on carbon emission efficiency in peri-metropolitan regions and offer empirical evidence for designing differentiated low-carbon policies within metropolitan systems.

Xinqin Liu, Runzhu Gu, Sujit Kumar Sikder et al.

The urbanisation process of recent decades has resulted in new urban structures that can be circumscribed by two standard concepts, namely the megacity and the metropolitan region. One common feature of these new structures is that cities/urban areas are becoming much larger in population as well as spatial size and continue to grow unabated – a trend of “mega-urbanisation”. The planning and administrative systems set up under the traditional urban-rural dichotomy no longer reflect the reality of settlement growth and therefore lead to a blurring of city boundaries and challenges in the management of urban areas. Here we make use of geospatial modeling and open-source data for a high-level spatial-linking approach across multiple scales and a long-term perspective in three distinct socio-economic settings, specifically Germany, Japan and China's Yangtze River Delta region and therefore visualize urban development trends over 45 years. Our mapping indicates that the emergence of megacities and metropolitan regions is primarily driven by endogenous industrial change, particularly between the secondary and tertiary sectors of the economy. Our findings shed new light on research in regional development and planning and demonstrate the need to go beyond the prevailing discussion that focuses on advanced producer services in the context of an ever-advancing globalisation process.

Ming Liu, Xiangye Yao, Lihua Sun

Urban logistics in metropolitan areas faces mounting pressure to deliver faster while controlling operational costs under strict fleet size constraints. Traditional vehicle routing models assume unlimited vehicle availability, overlooking realistic fleet utilization and spatial-temporal demand imbalances. This paper introduces the fleet-constrained metropolitan logistics problem (FCMLP), a novel framework integrating trunk linehaul scheduling, two-echelon routing, multi-trip operations, and anticipatory fleet positioning. We model the FCMLP as a Markov Decision Process capturing the stochastic and dynamic nature of metropolitan delivery flows. Our solution framework combines interpretable Bayesian Network-based demand forecasting for transparent proactive vehicle relocation decisions, parameterized cost-function approximation for dynamic order-to-linehaul assignment, and Adaptive Large Neighborhood Search for multi-trip vehicle routing. Computational experiments on synthetic instances and real-world data from a major e-commerce platform in Jakarta demonstrate 20–26% total cost reduction. Multi-trip operations alone reduce fleet size by 23%, while interpretable predictive relocation further improves performance by 7% through a 20% reduction in emergency deployments. The framework’s interpretability enhances operator trust and facilitates practical adoption, offering logistics platforms a path to improve vehicle utilization through operational efficiency and transparent predictive intelligence without expanding fleet size.

Marisol Flores-Garrido, Guillermo de Anda-Jáuregui, Plinio Guzmán et al.

Abstract Based on more than 11 billion geolocated cell phone records from 33 million different devices, daily mobility networks were constructed over a 15-month period for Greater Mexico City, one of the largest and most diverse metropolitan areas globally. The time frame considered spans the entire year of 2020 and the first three months of 2021, enabling the analysis of population movement dynamics before, during, and after the COVID-19 health contingency. The nodes within the 456 networks represent the basic statistical geographic areas (AGEBs) established by the National Institute of Statistics, Geography, and Informatics (INEGI) in Mexico. This framework facilitates the integration of mobility data with numerous indicators provided by INEGI. Edges connecting these nodes represent movement between AGEBs, with edge weights indicating the volume of trips from one AGEB to another. This extensive dataset allows researchers to uncover travel patterns, cross-reference data with socio-economic indicators, and conduct segregation studies, among other potential analyses.

Wichapol Chanchiewvichai, Suchada Rianmora, Nanthicha Patmayothin

This paper provides a detailed guide for Product Design and Development (PDD) of everyday essentials, with a focus on improving user accessibility. It applies Quality Function Deployment (QFD) principles to enhance user experiences by aligning design with customer requirements. Different customer types and their perceptions of everyday essential items are considered, with QFD used as a systematic approach to translate these needs into specific product characteristics, ensuring alignment with user expectations. The paper presents a step-by-step application of QFD on everyday essential design, highlighting key considerations and best practices. A case study on a drying and ironing device demonstrates how this approach encourages innovation and user-centric product design. The study focuses on metropolitan areas around Bangkok, Thailand, with customers aged 18 to 50, emphasizing design for limited spaces and addressing needs related to the rainy season or washing clothes at night. Results show no bad smell caused by bacteria. The key findings guide designers and developers to create products that prioritize user needs and preferences, enhancing overall usability and satisfaction. The contributions of this research benefit designers (manufacturers), customers, and researchers. The implications of this research include minimizing time spent on trial-and-error in the design stage, optimizing and reducing waste from the prototyping process. However, there is still a risk of distortion and loss in translating customers’ needs, highlighting the importance of receiving feedback after product use.

Valerie L Forman-Hoffman, Maddison C Pirner, Megan Flom et al.

BackgroundMental illness is a pervasive worldwide public health issue. Residentially vulnerable populations, such as those living in rural medically underserved areas (MUAs) or mental health provider shortage areas (MHPSAs), face unique access barriers to mental health care. Despite the growth of digital mental health interventions using relational agent technology, little is known about their use patterns, efficacy, and favorability among residentially vulnerable populations. ObjectiveThis study aimed to explore differences in app use, therapeutic alliance, mental health outcomes, and satisfaction across residential subgroups (metropolitan, nonmetropolitan, or rural), MUAs (yes or no), and MHPSAs (yes or no) among users of a smartphone-based, digital mental health intervention, Woebot LIFE (WB-LIFE). WB-LIFE was designed to help users better understand and manage their moods and features a relational agent, Woebot, that converses through text-based messages. MethodsWe used an exploratory study that examined data from 255 adults enrolled in an 8-week, single-arm trial of WB-LIFE. Analyses compared levels of app use and therapeutic alliance total scores as well as subscales (goal, task, and bond), mental health outcomes (depressive and anxiety symptoms, stress, resilience, and burnout), and program satisfaction across residential subgroups. ResultsFew study participants resided in nonmetropolitan (25/255, 10%) or rural (3/255, 1%) areas, precluding estimates across this variable. Despite a largely metropolitan sample, nearly 39% (99/255) resided in an MUA and 55% (141/255) in an MHPSA. There were no significant differences in app use or satisfaction by MUA or MHPSA status. There also were no differences in depressive symptoms, anxiety, stress, resilience, or burnout, with the exception of MUA participants having higher baseline depressive symptoms among those starting in the moderate range or higher (Patient Health Questionnaire-8 item scale≥10) than non-MUA participants (mean 16.50 vs 14.41, respectively; P=.01). Although working alliance scores did not differ by MHPSA status, those who resided in an MUA had higher goal (2-tailed t203.47=2.21; P=.03), and bond (t203.47=1.94; P=.05) scores at day 3 (t192.98=2.15; P=.03), and higher goal scores at week 8 (t186.19=2.28; P=.02) as compared with those not living in an MUA. ConclusionsDespite the study not recruiting many participants from rural or nonmetropolitan populations, sizable proportions resided in an MUA or an MHPSA. Analyses revealed few differences in app use, therapeutic alliance, mental health outcomes (including baseline levels), or satisfaction across MUA or MHPSA status over the 8-week study. Findings suggest that vulnerable residential populations may benefit from using digital agent–guided cognitive behavioral therapy. Trial RegistrationClinicalTrials.gov NCT05672745; https://clinicaltrials.gov/study/NCT05672745

Abubakr Ziedan, Candace Brakewood, Kari Watkins

Although the COVID-19 pandemic highly impacted transit ridership as people reduced or stopped travel, these changes occurred at different rates in different regions across the United States. This study explores the impacts of COVID-19 on ridership and recovery trends for all federally funded transit agencies in the United States from January 2020 to June 2022. The findings of this analysis show that overall transit ridership hit a 100-year low in 2020. Changepoint analysis revealed that June 2021 marked the beginning of the recovery for transit ridership in the United States. However, even by June 2022, rail and bus ridership were only about two-thirds of the pre-pandemic levels in most metropolitan statistical areas (MSAs). Only in a handful of MSAs like Tampa and Tucson did rail ridership reach or exceed 2019 ridership. This retrospective study concludes with a discussion of some longer-term changes likely to continue to impact ridership, such as increased telecommuting and operator shortages, as well as some opportunities, such as free fares and increased availability of bus lanes. The findings of this study can help inform agencies about their performance compared to their peers and highlight general challenges facing the transit industry.

Li Wang, Chengdong Xu, Maogui Hu et al.

Abstract Background Previous research pointed to a close relationship between the incidence of tuberculosis (TB) in aging populations and socio-economic conditions, however there has been lack of studies focused on a region of unbalanced socio-economic development. The aim of this paper is to explore the spatio-temporal variation in TB incidence and examine risk determinants of the disease among aging populations in a typical region. Methods Data on TB-registered cases between 2009 and 2014, in addition to social-economic factors, were collected for each district/county in Beijing, Tianjin and Hebei, a region characterized by an aging population and disparities in social-economic development. A Bayesian space–time hierarchy model (BSTHM) was used to reveal spatio-temporal variation in the incidence of TB among the elderly in this region between 2009 to 2014. GeoDetector was applied to measure the determinant power (q statistic) of risk factors for TB among the elderly. Results The incidence of TB among the elderly exhibited geographical spatial heterogeneity, with a higher incidence in underdeveloped rural areas compared with that in urban areas. Hotspots of TB incidence risk among the elderly were mostly located in north-eastern and southern areas in the study region, far from metropolitan areas. Areas with low risk were distributed mainly in the Beijing-Tianjin metropolitan areas. Social-economic factors had a non-linear influence on elderly TB incidence, with the dominant factors among rural populations being income (q = 0.20) and medical conditions (q = 0.17). These factors had a non-linear interactive effect on the incidence of TB among the elderly, with medical conditions and the level of economic development having the strongest effect (q = 0.54). Conclusions The findings explain spatio-temporal variation in TB incidence and risk determinants of elderly TB in the presence of disparities in social-economic development. High-risk zones were located mainly in rural areas, far from metropolitan centres. Medical conditions and the economic development level were significantly associated with elderly TB incidence, and these factors had a non-linear interactive effect on elderly TB incidence. The findings can help to optimize the allocation of health resources and to control TB transmission in the aging population in this region.

Natasha L. Miles, Kenneth J. Davis, Scott J. Richardson et al.

Abstract Background Networks of tower-based CO2 mole fraction sensors have been deployed by various groups in and around cities across the world to quantify anthropogenic CO2 emissions from metropolitan areas. A critical aspect in these approaches is the separation of atmospheric signatures from distant sources and sinks (i.e., the background) from local emissions and biogenic fluxes. We examined CO2 enhancements compared to forested and agricultural background towers in Indianapolis, Indiana, USA, as a function of season and compared them to modeled results, as a part of the Indianapolis Flux (INFLUX) project. Results At the INFLUX urban tower sites, daytime growing season enhancement on a monthly timescale was up to 4.3–6.5 ppm, 2.6 times as large as those in the dormant season, on average. The enhancement differed significantly depending on choice of background and time of year, being 2.8 ppm higher in June and 1.8 ppm lower in August using a forested background tower compared to an agricultural background tower. A prediction based on land cover and observed CO2 fluxes showed that differences in phenology and drawdown intensities drove measured differences in enhancements. Forward modelled CO2 enhancements using fossil fuel and biogenic fluxes indicated growing season model-data mismatch of 1.1 ± 1.7 ppm for the agricultural background and 2.1 ± 0.5 ppm for the forested background, corresponding to 25–29% of the modelled CO2 enhancements. The model-data total CO2 mismatch during the dormant season was low, − 0.1 ± 0.5 ppm. Conclusions Because growing season biogenic fluxes at the background towers are large, the urban enhancements must be disentangled from the biogenic signal, and growing season increases in CO2 enhancement could be misinterpreted as increased anthropogenic fluxes if the background ecosystem CO2 drawdown is not considered. The magnitude and timing of enhancements depend on the land cover type and net fluxes surrounding each background tower, so a simple box model is not appropriate for interpretation of these data. Quantification of the seasonality and magnitude of the biological fluxes in the study region using high-resolution and detailed biogenic models is necessary for the interpretation of tower-based urban CO2 networks for cities with significant vegetation.

Frederick G. Booth, Raymond R Bond, Maurice D Mulvenna et al.

Abstract Traditionally General Practitioner (GP) practices have been labelled as being in Rural, Urban or Semi-Rural areas with no statistical method of identifying which practices fall into each category. The main aim of this study is to investigate whether location and other characteristics can provide a tautology to identify different types of GP practice and compare the prescribing behaviours associated with the different practice types. To achieve this monthly open source prescription data were analysed by practice considering location, practice size, population density and deprivation rankings. One year’s data was subjected to k-means clustering with the results showing that only two different types of GP practice can be classified that are dependent on location characteristics in Northern Ireland. Traditional labels did not describe the two classifications fully and new classifications of Metropolitan and Non-Metropolitan were used. Whilst prescribing patterns were generally similar, it was found that Metropolitan practices generally had higher prescribing rates than Non-Metropolitan practices. Examining prescribing behaviours in accordance with British National Formulary (BNF) categories (known as chapters) showed that Chapter 4 (Central Nervous System) was responsible for most of the difference in prescribing levels. Within Chapter 4 higher prescribing levels were attributable to Analgesic and Antidepressant prescribing. The clusters were finally examined regarding the level of deprivation experienced in the area in which the practice was located. This showed that the Metropolitan cluster, having higher prescription rates, also had a higher proportion of practices located in highly deprived areas making deprivation a contributing factor.

Iacopo Prinetti, Caterina Cameli

Can the countryside offer a real alternative to metropolitan life? Today, rural areas are of­ten seen as places to ‘save’ through tourism and other discontinuous uses, but the era in which we live imposes a radical change of perspective: the pandemic has crumbled tourist economies and shown their fragility. The birth of a post-tourist society is particu­larly relevant in Italy, where entities such as the borghi are widespread: far and discon­nected from the large urban centers, they are nevertheless the archetype to which metro­politan areas are now turning again. To put these reflections into practice, it is effective to study a representative case: the ‘urban ter­ritory’ around San Benedetto del Tronto (AP), an ever-growing seaside tourist destination. The neighboring municipalities are nothing but dormitory districts, as evidenced by the new widespread urbanizations and the semi-abandoned historic centers of Acquaviva Pi­cena, Monteprandone, and Monsampolo del Tronto. Among the still evident signs of the 2016 earthquake and houses for sale, the three medieval villages spend in hibernation the months that separate the tourist sea­sons, calling for alternative scenarios: in or­der not to remain crystallized as monuments to culture and traditions, it is necessary for them to aspire to be places of daily life, in­serted in a network of biunivocal relations with other urban centers.

Walter Molinaro

In recent decades, climate change has become one of the most discussed topics within the territorial planning debates, both at European and Italian level. Urban and territorial planning addresses the topic in different ways according to the territorial and legislative context and according to the level of government of the territory involved. In the following article, firstly, the role of planning at European level in the fight against the negative effects of climate change is defined. Subsequently the focus is shifted to the Italian territorial context; in particular, to the role that the level of government of the metropolitan area, introduced in 2014 with the law 56/2014, better known as the Delrio Law, can play within these environmental challenges. Although the Italian metropolitan cities are widely differing in terms of territory, population and economy, they can represent, according to some visions, a potential pivot for the development of the entire nation. In 2017, Italian metropolitan cities signed the ''Bologna Charter'', a document that places them as protagonists of environmental protection and sustainable development. By means of this document, metropolitan cities undertake to counteract the negative effects of climate change by achieving eight macro objectives. The process of analysis of metropolitan cities and their planning tools has enabled the identification of virtuous metropolitan planning cases, which were found to be those of the Metropolitan Cities of Bologna, Milan and Venice. Subsequently, the actions that the three metropolitan cities have in order to achieve the eight objectives of the Bologna Charter, were analyzed. Precisely through this critical reading, it was possible to identify the best practices implemented. The topics most dealt within the metropolitan strategic plans are: sustainable mobility, energy efficiency, prevention of the effects of climate change, urban green areas and the protection of biodiversity. In relation to these issues, the three selected case studies implement noteworthy actions, which have been identified as possible models for other metropolitan bodies. The conclusion reached at the end of this analysis and comparison work, appears to be the belief that Italian metropolitan cities could actually play a coordinating role in climate change policies, promoting an integrated approach to spatial planning. To ensure that this result can be achieved, the promotion of a strong integration between the level of government of the metropolitan area and the local one is necessary. The latter, in fact, is indicated by supranational policies as the most suitable for dealing with the problem of climate change. The further conclusion reached concerns the importance of the mayor in this context. This figure is the most suitable for implementing the integration between the two levels of government of the territory. The Delrio Law establishes, indeed, that the mayors of the metropolitan bodies coincide with those of the main town.

S. Viswanathan, T. Imielinski

R. Engle, M. Watson

J. Masek, F. Lindsay, S. Goward

J. Oliver

J.-H. Park, O. K. Nayna, M. S. Begum et al.

Human activities are drastically altering water and material flows in river systems across Asia. These anthropogenic perturbations have rarely been linked to the carbon (C) fluxes of Asian rivers that may account for up to 40–50 % of the global fluxes. This review aims to provide a conceptual framework for assessing the human impacts on Asian river C fluxes, along with an update on anthropogenic alterations of riverine C fluxes. Drawing on case studies conducted in three selected rivers (the Ganges, Mekong, and Yellow River) and other major Asian rivers, the review focuses on the impacts of river impoundment and pollution on CO₂ outgassing from the rivers draining South, Southeast, and East Asian regions that account for the largest fraction of river discharge and C exports from Asia and Oceania. A critical examination of major conceptual models of riverine processes against observed trends suggests that to better understand altered metabolisms and C fluxes in <q>anthropogenic land-water-scapes</q>, or riverine landscapes modified by human activities, the traditional view of the river continuum should be complemented with concepts addressing spatial and temporal discontinuities created by human activities, such as river impoundment and pollution. Recent booms in dam construction on many large Asian rivers pose a host of environmental problems, including increased retention of sediment and associated C. A small number of studies that measured greenhouse gas (GHG) emissions in dammed Asian rivers have reported contrasting impoundment effects: decreased GHG emissions from eutrophic reservoirs with enhanced primary production vs. increased emissions from the flooded vegetation and soils in the early years following dam construction or from the impounded reaches and downstream estuaries during the monsoon period. These contrasting results suggest that the rates of metabolic processes in the impounded and downstream reaches can vary greatly longitudinally over time as a combined result of diel shifts in the balance between autotrophy and heterotrophy, seasonal fluctuations between dry and monsoon periods, and a long-term change from a leaky post-construction phase to a gradual C sink. The rapid pace of urbanization across southern and eastern Asian regions has dramatically increased municipal water withdrawal, generating annually 120 km³ of wastewater in 24 countries, which comprises 39 % of the global municipal wastewater production. Although municipal wastewater constitutes only 1 % of the renewable surface water, it can disproportionately affect the receiving river water, particularly downstream of rapidly expanding metropolitan areas, resulting in eutrophication, increases in the amount and lability of organic C, and pulse emissions of CO₂ and other GHGs. In rivers draining highly populated metropolitan areas, lower reaches and tributaries, which are often plagued by frequent algal blooms and pulsatile CO₂ emissions from urban tributaries delivering high loads of wastewater, tended to exhibit higher levels of organic C and the partial pressure of CO₂ (<i>p</i>CO₂) than less impacted upstream reaches and eutrophic impounded reaches. More field measurements of <i>p</i>CO₂, together with accurate flux calculations based on river-specific model parameters, are required to provide more accurate estimates of GHG emissions from the Asian rivers that are now underrepresented in the global C budgets. The new conceptual framework incorporating discontinuities created by impoundment and pollution into the river continuum needs to be tested with more field measurements of riverine metabolisms and CO₂ dynamics across variously affected reaches to better constrain altered fluxes of organic C and CO₂ resulting from changes in the balance between autotrophy and heterotrophy in increasingly human-modified river systems across Asia and other continents.