•Modeling dynamic congestion in ride-sharing systems with a trip-based MFD model.•Investigating how willingness to share influences shared rides and dynamic congestion.•Understanding quantitatively ...the effect of fleet size in congestion.•Developing elegant parking management strategies to prevent idle vehicles from cruising.•Analyzing day-to-day dynamics for drivers’ participation in the service.
The advent of shared-economy and smartphones made on-demand transportation services possible, which created additional opportunities, but also more complexity to urban mobility. Companies that offer these services are called Transportation Network Companies (TNCs) due to their internet-based nature. Although ride-sourcing is the most notorious service TNCs provide, little is known about to what degree its operations can interfere in traffic conditions, while replacing other transportation modes, or when a large number of idle vehicles is cruising for passengers. We experimentally analyze the efficiency of TNCs using taxi trip data from a Chinese megacity and an agent-based simulation with a trip-based MFD model for determining the speed. We investigate the effect of expanding fleet sizes for TNCs, passengers’ inclination towards sharing rides, and strategies to alleviate urban congestion. We observe that, although a larger fleet size reduces waiting time, it also intensifies congestion, which, in turn, prolongs the total travel time. Such congestion effect is so significant that it is nearly insensitive to passengers’ willingness to share and flexible supply. Finally, parking management strategies can prevent idle vehicles from cruising without assigned passengers, mitigating the negative impacts of ride-sourcing over congestion, and improving the service quality.
Siregar ES, Pasaribu N, Lubis AF. 2023. Diversity of epiphytic bryophytes in Medan City Parks, North Sumatra, Indonesia and its potential as lead (Pb) bio-accumulators. Biodiversitas 24: 3214-3221. ...The information on the diversity of epiphytic bryophytes in the metropolitan area, particularly Medan City, North Sumatra, Indonesia has been limited. Therefore, this study aimed to conduct an inventory of the diversity of epiphytic bryophytes in Medan City parks as well as to assess their potential as lead (Pb) bioaccumulators. Three sampling sites, namely Ahmad Yani Park, Beringin Park, and Medan Zoo, were selected based on their pollution levels from high to low, respectively. Five plots with dimensions of 25×25 m were placed at each site and five representative host trees were selected in each plot. Lead (Pb) bioaccumulation of bryophyte samples is determined using the atomic absorption spectroscopy (AAS) method at the Plant Research Center Laboratory, Medan. The Pb-bioaccumulation capacity of each species from different sites was compared through two-way ANOVA. The results showed eight species, namely four liverworts (Marchantiophyta): Cololejeunea lanciloba Steph., Lejeunea cocoes Mitt., Lopholejeunea eulopha (Taylor) Schiffn., and Lopholejeunea subfusca (Nees) Schiffn., as well as 4 Mosses (Bryophyta): Calymperes tenerum C.Müller, Meiothecium microcarpum Mitten, Octoblepharum albidum Hedwig and Vesicularia dubyana Brotherus. Vesicularia dubyana was the dominant species at Beringin Park and Medan Zoo, while C. tenerum was dominant at Ahmad Yani Park. The biodiversity of epiphytic bryophytes in this study was categorized as moderate level (1?H’?3). The highest Important Values Index (IVI) of epiphytic bryophytes in this study was obtained for V. dubyana at 131.80. The highest Pb bioaccumulation was observed in O. albidum at 87.5 mg/kg, followed by V. dubyana at 66.6 mg/kg. This study provided information on the ecological contribution of epiphytic bryophytes as Pb bioaccumulators in urban areas. Vesicularia dubyana and O. albidum can be recommended as biomonitoring agents in the future.
•Designing one-of-a-kind experiment to monitor urban congestion with a swarm of drones.•Creating the most complete urban multimodal dataset, nicknamed pNEUMA, to study congestion.•Investigating ...traffic phenomena at different scales of modeling.•Developing an open science initiative with almost half a million trajectories for transportation-oriented research.
The new era of sharing information and “big data” has raised our expectations to make mobility more predictable and controllable through a better utilization of data and existing resources. The realization of these opportunities requires going beyond the existing traditional ways of collecting traffic data that are based either on fixed-location sensors or GPS devices with low spatial coverage or penetration rates and significant measurement errors, especially in congested urban areas. Unmanned Aerial Systems (UAS) or simply “drones” have been proposed as a pioneering tool of the Intelligent Transportation Systems (ITS) infrastructure due to their unique characteristics, but various challenges have kept these efforts only at a small size. This paper describes the system architecture and preliminary results of a first-of-its-kind experiment, nicknamed pNEUMA, to create the most complete urban dataset to study congestion. A swarm of 10 drones hovering over the central business district of Athens over multiple days to record traffic streams in a congested area of a 1.3 km2 area with more than 100 km-lanes of road network, around 100 busy intersections (signalized or not), many bus stops and close to half a million trajectories. The aim of the experiment is to record traffic streams in a multi-modal congested environment over an urban setting using UAS that can allow the deep investigation of critical traffic phenomena. The pNEUMA experiment develops a prototype system that offers immense opportunities for researchers many of which are beyond the interests and expertise of the authors. This open science initiative creates a unique observatory of traffic congestion, a scale an-order-of-magnitude higher than what was available till now, that researchers from different disciplines around the globe can use to develop and test their own models.
•Developing a static clustering that minimises heterogeneity and guarantees connectivity.•Formulating and solving an MILP that truncates a feasible set of snakes with the aforementioned ...objectives.•Extending the method to dynamic clustering that considers spatial interactions.•Merging or Splitting allows for a better fine-tuning in the dynamic framework.•Fast computation and proper integration of physical properties of congestion propagation.
The problem of clustering in urban traffic networks has been mainly studied in static framework by considering traffic conditions at a given time. Nevertheless, it is important to underline that traffic is a strongly time-variant process and it needs to be studied in the spatiotemporal dimension. Investigating the clustering problem over time in the dynamic domain is critical to better understand and reveal the hidden information during the process of congestion formation and dissolution. The primary motivation of the paper is to study the spatiotemporal relation of congested links, observing congestion propagation from a macroscopic perspective, and finally identifying critical pockets of congestion that can aid the design of peripheral control strategies. To achieve this, we first introduce a static clustering method to partition the heterogeneous network into homogeneous connected sub-regions. The proposed framework guarantees connectivity of the cluster in different steps, which eases the development of a dynamic framework. The proposed clustering approach has 3 steps; firstly, it obtains a set of homogeneous connected components in the network. Each component has a form of sequence which is built by sequentially adding neighboring links with similar level of congestion. Secondly, the major skeleton of clusters is obtained out of this feasible set by minimizing a heterogeneity index. Thirdly, a fine-tuning step is designed to complete the clustering task by assigning the unclustered links of the network to proper clusters while keeping the connectivity. The optimization problem in both second and third step is formulated as a mixed integer linear programming. The approach is also extended to capture spatiotemporal growth and formation of congestion. The dynamic clustering is based on an iterative and fast procedure that considers the spatiotemporal characteristics of congestion propagation and identifies the links with the highest degree of heterogeneity due to time dependent conditions and finally re-cluster them to guarantee connectivity and minimize heterogeneity. An implementation of the developed methodologies in a megacity based on more than 20,000 taxis with GPS highlights the quality of the method due to its fast computation and proper integration of physical properties of congestion.
The factors that account for the differences in the economic productivity of urban areas have remained difficult to measure and identify unambiguously. Here we show that a microscopic derivation of ...urban scaling relations for economic quantities vs. population, obtained from the consideration of social and infrastructural properties common to all cities, implies an effective model of economic output in the form of a Cobb-Douglas type production function. As a result we derive a new expression for the Total Factor Productivity (TFP) of urban areas, which is the standard measure of economic productivity per unit of aggregate production factors (labor and capital). Using these results we empirically demonstrate that there is a systematic dependence of urban productivity on city population size, resulting from the mismatch between the size dependence of wages and labor, so that in contemporary US cities productivity increases by about 11% with each doubling of their population. Moreover, deviations from the average scale dependence of economic output, capturing the effect of local factors, including history and other local contingencies, also manifest surprising regularities. Although, productivity is maximized by the combination of high wages and low labor input, high productivity cities show invariably high wages and high levels of employment relative to their size expectation. Conversely, low productivity cities show both low wages and employment. These results shed new light on the microscopic processes that underlie urban economic productivity, explain the emergence of effective aggregate urban economic output models in terms of labor and capital inputs and may inform the development of economic theory related to growth.
Ecosystem services are present everywhere, green vegetation coverage (or green areas) is one of the primary sources of ecosystem services considering urban areas sustainability and peoples urban life ...quality. Urban vegetation cover loss decreases the capacity of nature to provision ecosystem services; the loss of urban vegetation is also observed within the Amazon. This study aims at identifying urban vegetation loss and relate it to the provision of ecosystem services of reduction of air quality, reduction of air pollution, and climate regulation. Urban vegetation coverage loss was calculated using NDVI on LANDSAT 5 imagery over a 23-year period from 1986 to 2009. NDVI thresholds were arbitrarily selected, and complemented by in locus observation, to establish guidelines for quantitative (area) and qualitative (density) evolution of green cover, divided in six different categories, named as water, bare soil, poor vegetation, moderate vegetation, dense vegetation and very dense vegetation. Data on air pollution, noise pollution and temperature were outsourced from previous works. Measurement show a significant loss of very dense, dense and moderate vegetation coverage and an increase in poor vegetation and bare soil areas, in accordance to increase in air and noise pollution, and local temperature, and provides positive refashions between the loss of urban green coverage and decrease in ecosystem services.
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•Significant urban vegetation coverage loss.•Decline in the provisioning of ecosystem services.•Absence of action to recover and monitor green areas.
Background: The nutritional status of the child can be measured by using anthropometry which is the valuable tool and the gold standard method. The magnitude of different measures of nutritional ...status is affected by choice of reference charts used. Objective: To compare the world Health Organization growth charts with Indian academy of pediatrics growth charts to assess the malnutrition among under 5 children attending Urban health center of a medical College. Methodology: A cross sectional study was conducted among 220 children attended urban health centre of SS. Institute of Medical Sciences for a period of 4 months. Height and weight were measured and plotted on World Health Organization and Indian Academy of Pediatrics charts. Results: In this study underweight was detected among 46.9% of the boys and 43.8% of the girls and stunting was detected among 50.4% of the boys and 43.8% of the girls by using World Health Organization Growth Charts. According to Indian academy of Pediatrics, 32.1% of the boys and 38% of the girls were found to be undernourished and Stunting was detected among 53.9% of the boys and 68.8% of the girls. Conclusion: In this study both the growth charts showed variation in the height and weight measurements.
The main hypothesis of this study was that the microplastic (MP) concentration would be higher in the city centre. The MP (<5 mm) abundance and distribution in the urbanized section of the Vistula ...River were examined. Samples were collected from three different sites: 1) the less urbanized part of the city, 2) the area close to the tributary outlet and wastewater treatment plant (WWTP), and 3) the city centre. The abundance of MPs in water ranged from 1.6 to 2.55 items L−1, whereas in the sediments, it varied from 190 to 580 items kg−1. The highest MP concentration was observed in the water collected in the city centre. However, in the case of sediments, the most polluted sample was collected from a sampling point located near the WWTP and tributary outlet. The diversity of the MPs abundance along the river was associated with the hydrological and sedimentological conditions, which was confirmed by the grain size analysis of sediments. The dominant type of MPs in both the water and sediment samples was fibre. The MPs were characterized by Raman spectroscopy as polystyrene (PS), polypropylene (PP), and a variety of other materials with different levels of deterioration. The images obtained by scanning electron microscopy (SEM) showed different disintegration features. Moreover, the SEM analyses revealed the occurrence of adhered particles and diatoms on the surface of MPs. The adsorption of various elements onto the MPs surface and the adhered particles was confirmed by energy-dispersive X-ray spectroscopy. The conducted studies emphasized the significance of the impact of large urban agglomerations, such as the Warsaw metropolitan area, on the concentration of MPs in rivers. Further studies are needed to better assess, for instance, the precise mode through which MPs in urban regions are transported by rivers to the seas.
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•First studies of microplastics in the urban section of the longest river in Poland.•Microplastics abundance seems to be correlated with the population density.•Fibres are the most common type of microplastics in this area.•Raman and IR spectroscopy enable microplastics characterization and classification.•Adhered particles and metals on the debris surface were analysed with SEM-EDS.
The aim of the article is to present the communication by public transport of the towns located within the boundaries of the Municipal Functional Area of Słupsk–Ustka (MOF S–U) with the core cities ...(Słupsk and Ustka) and to indicate the areas where the phenomenon of transport exclusion may occur. The public transportation network in the area does not meet the needs directed by the residents to local authority decision-makers, which may limit their ability to get around, especially on weekends. During the study, the literature on the subject, documents at local and regional levels, and data contained in timetables were analysed as well as the GIS visualisations were used. Insufficient communication with public transport in the area results in limited transport accessibility and, consequently, may lead to transport exclusion.
With the fast development of urbanization and motorization, an increasing number of people choose to buy private cars to fulfill their daily travel needs. In particular, many people from various ...positions of the city drive their cars to specified areas, and then they will stop and stay for a certain period of time, leading to a spatiotemporal evolution of urban area attractiveness (AA). In this paper, we aim at understanding urban AA based on analyses of private car trajectory datasets. Specifically, by extracting point-of-stop (PoS) data from the private car trajectories, we design the variational Bayesian Gaussian mixture models (VBGMM) to deduce the probability density distribution of PoSs and connect it to the variation of AA. We establish a deep learning model based on long short-term memory (LSTM) to capture the evolution of the AA. Furthermore, we integrate dropout in the LSTM method to address challenging issues such as overfitting and time-consuming training of complex neural networks in the AA prediction. We conduct experiments by using real-world private car trajectory data to evaluate the performance of the proposed method. The results validate that our proposed method outperforms existing ones in terms of various metrics. To the authors' knowledge, our work is the first one to utilize private car trajectory data to study urban area attractiveness, thereby facilitating a new perspective regarding an understanding of human travel behavior and the evolution of urban mobility.
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