Stations In Area Research Articles

Classifying station areas in greater Manchester using the node-place-design model: A comparative analysis with system centrality and green space coverage

Transit-oriented development (TOD) is receiving increasing attention from planners and policymakers as an essential strategy for addressing urban travel inequalities and air pollution. As an analytical method based on the conceptual construct of TOD, the node-place-design (NPD) model is utilized by researchers to assess TOD in urban public transport systems. However, current research prioritizes local perspectives of station development and fails to identify the functions of stations at the system level. In addition, few TOD-related analyses have considered the ecological aspects of cities. In the present study, we used an NPD model to evaluate TOD development at rail stations in Greater Manchester. We incorporated extended indicators of systemic importance and green space coverage in our analysis to provide additional insight into the model. First, we found a low level of TOD integration around stations in Greater Manchester, and some differences in development levels around train stations and Metrolink stations. Second, a comparison with the extended system importance indicators revealed the potential for significant differences in the NPD index and the system importance indicators of stations. This identified some stations that have the potential to take on new routes and some areas that are worthy of transit-oriented development. Finally, we found a specific negative correlation between the NPD index and the green space indicator. This indicated that the TOD model sacrifices green space to a certain extent and demonstrated the importance of including ecological indicators in the TOD assessment. The present study provides additional insight into the NPD model by introducing extended systemic and ecological indicators.

Measuring the influence of transit accessibility on housing and transportation expenditures in the U.S.: A propensity score matching approach

This study quantified the extent to which transit accessibility has an impact on housing and transportation expenditures of households in the U.S. (the treatment effect). This study used propensity score matching (PSM) to construct transit station areas (TSAs) and corresponding non-TSAs with similar observed characteristics, including built environment features and socio-economic characteristics of CBGs, and then employed paired t-tests to estimate the treatment effect. This study revealed that homeowners in TSAs spent 1,595 dollars more on housing expenditures and saved 493 dollars on transportation expenditures annually compared to those in non-TSAs. Also, the annual rent costs of TSAs and non-TSAs in the U.S. were about 15,990 and 14,993 dollars, while the annual transportation costs of TSAs and non-TSAs were approximately 13,151 and 13,644 dollars. This study contributes to an understanding of how transit accessibility in the U.S. was associated with the housing and transportation affordability of locations.

Comparison of acetylcholinesterase among employees based on job positions and personal protective equipment in fuel station.

The purpose of this study was to compare the levels of acetylcholinesterase (AChE) among employees based on job positions and the wearing of personal protective equipment (PPE) in fuel station areas. The sample group consisted of 200 people sorted into various groups, including (i) Inside fuel dispenser area (I-FDA) group consisting of 100 employees for refueling, cashier, and loading fuel into storage tanks, and (ii) Outside fuel dispenser area (O-FDA) group, consisting of 100 employees working in convenience stores, food stores, coffee shops, and offices, as well as general staff and car washers. Data were collected using interview questionnaires and blood samples were analyzed for AChE activity. The results showed that the I-FDA group had a significantly lower mean of serum AChE (7.38±1.73 U/ml) than the O-FDA group (7.85±1.49 U/ml) (p<0.05). The I-FDA group had a 2.43 times higher risk of abnormal serum AChE than the O-FDA group (OR=2.43, 95%CI=1.05-5.60). When considering the risk factors for job positions, it was found that refueling and cashier positions had lower AChE activity levels than those who did not (p<0.05). In the part, employees for food sales in a closed building and those wearing PPE masks had significantly higher AChE activity levels than those who did not or who wore them (p<0.05). Based on the aforementioned, employers at fuel stations should strictly determine the appropriate measures for wearing a PPE mask. Further, employees should be provided accommodation away from oil supply or enclosed buildings during breaks to reduce the effects on the neurotransmitter.

Spatial analysis and hazard assessment of large-scale ancient landslides around the reservoir area of Wudongde hydropower station, China

Spatial analysis and hazard assessment of large-scale ancient landslides around the reservoir area of Wudongde hydropower station, China

Transit-Oriented Development in China: A Comparative Content Analysis of the Spatial Plans of High-Speed Railway Station Areas

With rapid high-speed railway (HSR) developments in China, HSR-based transit-oriented development (TOD) has proliferated across the country. Although local governments claim that HSR station areas are planned according to TOD principles, some scholars argue that these station areas actually contribute to unsustainable development. This study investigates two main questions: (1) what success factors should be included in a TOD plan for HSR station areas? (2) to what extent are these factors considered in the plans of Chinese HSR station areas? To answer these questions, we use content analysis to compare spatial plans for 15 HSR station areas across China, triangulating the findings via in-depth interviews and field investigations. This study reveals that most of the factors in the plans for HSR station areas deviate from TOD principles, especially in small- and medium-sized cities. We find that Chinese local governments mainly use TODs as a tool to promote suburban expansion around HSR stations.

Developing a TOD assessment model based on node–place–ecology for suburban areas of metropolitan cities: A case in Odawara

Transit-oriented development (TOD) has a close relationship with ecology since its inception and aims to create livable and sustainable environments. However, few studies have examined the key point of ecology in the construction of TOD assessment models. This paper takes Odawara as an example, a city located on the outskirts of the Tokyo metropolitan area. Based on the node–place model, a new dimension of ecology is introduced to expand the two-dimensional model into a three-dimensional model, primarily applied to 18 stations in Odawara. Using this model, the study explores the impact of TOD on the development process of Odawara and proposes historical policy and data-based current condition discussions. The results indicate that the model-based analysis reveals a discrepancy between the current condition of the 18 stations in Odawara and the official positioning of these stations by city managers. Additionally, there is a negative correlation between the node–place value and ecology value of the station areas. We believe that this approach not only directly connects TOD with ecological considerations but also develops a new quantitative assessment model for TOD, particularly in the context of abundant ecological resources in suburban areas of metropolitan areas, arriving at a more refined level of research than before. At the same time, the model continues to maintain good scalability, providing new perspectives for the metabolism of developing areas worldwide.

Study on Dynamic Load of Air-Conditioning System in Subway Station Based on Hourly Passenger Flow

The research focuses on the air-conditioning system in a public area of a subway station. To address this, an optimization model based on the grid time segmentation method was constructed, specifically a GM (1,1) model. We explored the influence of the hourly passenger flow fluctuation on the load of the subway air-conditioning system, obtained the dynamic change law of the air conditioning system load in the subway station, and then dynamically adjusted the air conditioning system according to the dynamic change law to reduce the operation energy consumption of the system. Through the analysis of the simulation results, the model predicted that compared with the actual passenger flow data, the average maximum relative error was 14.97%. On this basis, the change law of the dynamic load of the subway air-conditioning system which caused by the change in passenger flow from time to time could be calculated and analyzed. Compared with the calculated load of the air conditioning system, the working day load was decreased by 1469.77 kW, or 22.00%. The findings indicate that in response to the dynamic load of fluctuations, timely adjustment of the air supply parameter of the air-conditioning system offers a significant reference point for optimizing energy efficiency in subway stations.

A Low Voltage Prediction Based on LSTM-BP Combined Model for Distribution Station Areas

The timely management of low voltage issues in the distribution network relies heavily on accurate predictions of voltage in the station areas. Many current methods for voltage prediction require complex data collection involving power grid topology parameters and electricity information. However, these methods suffer from drawbacks such as the need for extensive data, limited real-time performance, and significant prediction errors. Hence, this study proposes an approach to voltage prediction utilizing a combined LSTM-BP model. Initially, an analysis of the mechanism of low voltage formation in the station areas reveals that the primary factor influencing node points voltage is the power consumption of users. Subsequently, the LSTM neural network is employed to forecast short-term load curves in the distribution station areas, while the self-learning capability of the BP neural network is utilized to establish the correlation between users’ power and their corresponding voltage levels. By effectively combining the above two neural network models, the historical load’s data can be used to accurately and quickly predict the future low voltage situation in the station areas. Finally, taking station areas as the research object and comparing the actual voltage data with the voltage data predicted in this paper, the results show that within the 1V error range, the prediction accuracy is 99.8%. In contrast to the conventional voltage prediction approach, the method put forward in this research paper enables instantaneous and precise anticipation of low voltage levels without relying on details such as station configuration, line characteristics, or user voltage information.

Load Identification of Low-voltage Station Area Based on Power Metering Sensor and Deep Reinforcement Learning

Load Identification of Low-voltage Station Area Based on Power Metering Sensor and Deep Reinforcement Learning

Optimization Method for Land Use of the Xi’an Rail Transit Station Area Based on a Multi-Objective Model

For the intensive, efficient, and sustainable utilization of land resources, it is of great significance to optimize the spatial allocation of different types of land use intensity in rail transit station areas. The current land use optimization model has some shortcomings in objective function, constraint conditions, and the solution process. In response to this, a new multi-objective optimization model for rail transit station land use was built. With station space efficiency as the starting point, the three objectives of the model optimization were the traffic volume, environment quality, and land balance of the rail transit station, and the constraint conditions were the plot ratio, environment quality, and efficiency level. Lingo was used to solve the optimal plot ratio of different types of land use intensity. Compared with the non-inferior solution of the rail transit station area multi-objective original model, the ideal plot ratio of various land uses obtained by the optimized new model was more reasonable. There was a relatively large gap between the non-inferior solutions of some original models and the actual conditions. In contrast, the optimized new model had stronger maneuverability. The deviation ranges of the two models were −0.4% to 0.9% on the residential land plot ratio adjustment index, −3.2% to 4.8% on the public land plot ratio adjustment index, and 1.1% to 1.9% on the commercial land plot ratio adjustment index. This research aimed to provide a basis and reference for the land use and planning of Xi’an rail transit station.

Comparison of Prevalence and Associated Factors of Multisystem Health Symptoms Among Workers in the Gas Station Area, Thailand

This cross-sectional study aimed to compare the prevalence of multisystem health symptoms (MHS) of workers in gas station areas before and after their employment and examine the factors affecting the MHS of workers. Data were collected by an interview questionnaire from 200 workers inside and outside refueling areas at eight gas stations in Rayong Province, Thailand. This study found that employees had a statistically significant increase in the prevalence of current MHS in comparison to before starting work (p-value&lt;0.05), with 31.5%. Working overtime for more than 6 hours per week led to respiratory symptoms (OR = 2.63, 95% CI = 1.14–6.07) and psychological symptoms (OR = 2.69, 95% CI = 1.12–6.49). Wearing respiratory protective equipment for less than three hours affected ear/throat/nose systems (OR = 4.26, 95% CI = 1.43–12.65). Petrol refueling resulted in liver (OR = 2.32, 95% CI = 1.4–12.65) and eye symptoms (OR = 2.57, 95% CI = 1.10–5.39). Therefore, gas station owners should set up enclosed rooms to reduce the duration of fuel exposure, and workers should wear personal protective equipment when refueling or near the dispenser.

Does metro expansion matter? Metro network enhances metro mode share of commuters living away from stations, but not those near stations

As the metro system grows from a single line to a network of multiple lines, how does the expansion affect metro mode share of commuters residing near and away from stations? This study attempted to uncover the mechanism of commuters’ mode choice after the expansion. We employed two waves of household travel survey data, before and after the formation of the metro network in Xi’an, to develop a difference-in-difference model. We found that after the metro network formed, the average metro mode share of residents within 1 km of metro stations increased slightly but the change was statistically insignificant. This is because the average share was smaller around the stations of newer metro lines. By contrast, the average metro mode share of residents living beyond 1 km from metro stations grew substantially, likely because of the increase of workplaces within station areas and the improvement in first-/last-mile connection services. To achieve low-carbon transport, this study underscores using metro lines to connect key destinations, densifying employment around metro stations, and promoting access to metro stations through convenient feeder buses, shared micro-mobility, and pedestrian-friendly design.

Экологическая оценка варьирования состава травянистого покрова по контрастным элементам мезорельефа Лесной Опытной Дачи РГАУ-МСХА имени К.А. Тимирязева

The present paper analyzes the results of a comparative ecological study of regional typological patterns of spatial variability of the herbaceous cover composition in the conditions of a gently sloping mesorelief at the Forest Experimental Station of the Russian Timiryazev State Agricultural University – the background object of environmental monitoring for the northern part of the Moscow metropolis. Standardized descriptions of the composition and biodiversity assessments of the vegetation cover are presented on five representative sites of the orographic transect, cutting in the direction from northeast to southwest the gently sloping moraine hill dominating in the mesorelief and its opposite slopes of the northeastern and southwestern exposures, including their foots – with a total height difference not more than 15 meters. The greatest variety of herbaceous species from the 20 families represented in the studied plots was found at the foot of slopes with more stable humidification conditions, and its minimum level was at the summit of a moraine hill with pronounced summer desiccation of the topsoil of the zonal sod Podzoluvisols characteristic for the Forest Experimental Station. Other important ecological factors of herbaceous biodiversity are the exposure and shape of the slope, which affect both the temperature regime and the seasonal dynamics of the topsoil moisture – under conditions of relatively insignificant variation in the tree canopy density and pronounced recreational load on the ground vegetation and topsoil. Humus-podzolic soils dominating on the bottom of the slope of the north-eastern exposure with a steadily increased moisture level are characterized by reduced resistance to recreational load, which leads to the maximum severity of the pathway network and relatively reduced biodiversity indices. The analysis of the patterns of spatial variation in the composition of the herbaceous cover allowed one to identify the problematic environmental situations and factors of reducing its biodiversity, that has to be taken into account when further planning the regulation of recreational load at the Forest Experimental Station and similar areas of the forest infrastructure of the northern part of Moscow, as well as when assessing the projected anthropogenic impact in the conditions of the Moscow megalopolis and comparable urban ecosystems of the southern taiga and mixed-forest subzones at the European territory of Russia. Keywords: BIODIVERSITY, URBAN FOREST PARKS, FOREST ECOSYSTEMS, MOSCOW, IMPACT ASSESSMENT, RECREATIONAL LOAD, HERBACEOUS COVER, ENVIRONMENTAL FACTORS, URBAN ECOSYSTEMS

Evaluation of Sustainable Development Potential of High-Speed Railway Station Areas Based on “Node-Place-Industry” Model

The development of the HSR station area is the result of the combined effect of the three elements of transport, place, and industry. This study introduces the industrial dimension and constructs the node-place-industry model to empirically analyze the development potential of station areas along the Hunan section of the Beijing–Guangzhou and the Shanghai–Kunming high-speed railway lines. The results show that (1) the development of the three spatial elements of the station area is mostly out of sync, and the node value has the highest fit with the integrated potential value of the station area; (2) there is a significant correlation between the magnitude of the combined potential of the station area and the site location, station class and time of development; (3) according to the results of the cluster analysis, it was found that most of the stations were in a state of disequilibrium, and the main reason was that the functional value of the place did not match with the value of industrial aggregation. In particular, the introduction of the industry dimension extends the NP model and establishes a tessellated analytical framework for station type classification, providing an interesting assessment tool for the sustainable development of transport hub areas.

How do walking environments along the connecting path affect the disparity in public bicycle usage among multiple docking stations around tube stations?

The integration of public bicycles with tube systems has the potential to enhance urban transportation sustainability and efficiency. However, the utilization of public bicycles can significantly differ among various docking stations, even when they fall within the coverage area of the same tube station. Understanding the factors that attract or discourage individuals from using public bicycles in different locations is essential for informed decision-making regarding infrastructure and policy enhancements. This study examines the disparity in public bicycle usage, with a specific focus on the micro-level walking environments along connecting paths between docking stations and tube stations. Transaction data collected from London public bicycle and tube systems are utilized, alongside micro-level walking environment and macro-level built environment and socio-economic factors. A generalized additive mixed model is employed to capture nonlinear effects and spatial autocorrelations in docking station usage.The results reveal significant effects of walking environments along connecting paths on docking station usage. Specifically, positive associations are observed between bicycle station usage and footpaths quality, presence of pedestrian crossing, and points of interests (e.g., green space) along the connecting path, as well as tube ridership, cycle facilities, and land-use mixture. Conversely, negative relationships are observed with walking distance, physical barriers, road crossed, and bus stops. Moreover, proximity to transit, distance to the city center, and deprivation level demonstrate threshold effects on bicycle station usage. This study provides several practical implications for improving the multi-mode transportation system and the planning of docking stations around tube station, aiming to create cycling-friendly and transit-oriented environments.

Tracing complex urban transformations in Germany, Switzerland and Austria using trajectory-based qualitative comparative analysis (TJ-QCA)

The re-development of abandoned industrial areas and city cores characterizes the transition from industrial to post-industrial societies in Western Europe. Shorter-term and project-based urban programs, like the re-developments of waterfronts and station areas, emerged as more sui in response to the consequences of economic, demographic, political and cultural change than long-term, top-down spatial planning. Notably, processes and outcomes of strategic spatial planning vary across European cities and may display unique characteristics. This study compares eleven urban transformations in Germany, Austria, and Switzerland to shed light on the degree to which these programmatic urban transformations have been successful in shifting the urban fabric from an industrial to a post-industrial state. We examine the combinations of factors that, over time, have contributed to a qualitative urban change. Using primary and secondary sources, we perform a Trajectory-Based Qualitative Comparative Analysis (TJ-QCA) to identify recipes for successful urban transitions. Results show that there are two main planning recipes associated with successful urban transformations: either a combination of a high strategic character of the project with a leading role of public actors, or a combination of a high strategic character with brownfield redevelopment.

URBAN ENVIRONMENTAL FLOOD SUSCEPTIBILITY USING A MULTI-LAYERED NEURAL NETWORK MODEL FROM SATELLITE IMAGERY SOURCES

&lt;p&gt;Recently, there has been a rise in research based on data-driven based machine learning models to address the issue of processing speed posed by various physiological simulations. The majority of studies, however, have concentrated on creating models for particular water sources, drainage systems, and gauge stations area. Therefore, unless further data is supplied and the models are subsequently trained, their outcomes cannot be effectively applied to different scenarios. With its excellent spatio-temporal accuracy range with the advanced analytics, the forthcoming Global Navigations Satellite Systems (GNSSs) technology offers a novel method for the monitoring of flood disasters in dynamic manner. This study recommends a Multi-layered Neural Network (MNN) for flood monitoring, which combines a Convolutional Neural Networking (CNN) along with a backward propagation based (BP) learning network. The CNN component is used to obtain the abstracted features from full delay doppler maping images. The BP section is provided with GNSSs characteristics, such as reflection of surface with power range, and also the vegetation attributes from the Soil Moistening Active Passives (SMAP) satellite source data. In comparison to physiologically based models, the results shown that the CNN-oriented system makes accurate predictions on "unseen" areas of catchment with a substantially shorter processing time. The obtained results imply that, with respect to accuracy of prediction, the patch-enabled option is superior to the resizing-based option. Additionally, every experiment has demonstrated that the forecast of flow speed is more precise than the prognosis of water depth, indicating that the water deposition is more complex to information about global level elevations than the flow speed with velocity.&lt;/p&gt;&#x0D;

EFFECT OF NP DOSES BY NEW CaCO3 AGROFUNDS ON THE FORMATION OF SOYBEAN YIELDS

For the acid soils in the south of the country, it is more than necessary to apply calcareous amendments. Results in this sense were obtained over the years at the main crop plants in the station area. Considering the increasing importance of the soybean crop, it was considered necessary to resume these types of research, as new products based on limestone and dolomite appeared. Significant results were obtained by forming the total biomass of the plant as well as its components. In the case of the Cristina TD (00) variety, the interaction between several CaCOɜ formulations and NP fertilizers contributed as follows: plant biomass 6.46 t/ha (100%), pod biomass 4.16 t/ha (63%), and grains were 2.17 (33%). Of the two analyzed factors, NP fertilizer had the most important contribution to this variety, followed by the influence of the four CaCOɜ formulations. The interaction between the two factors was always negative demonstrating that there was some competition between the cations. The obtained correlations were in all cases positive, but of different intensities. Through the obtained results, it is recommended that new formulations of CaCOɜ be permanently used in the soybean cultivation technology on acid soils.

Possibilities Study of a Non-condensable Gas Exhaust System through the Condensate Injection Pipe at PLTP Wayang Windu

Wayang Windu Geothermal Power Plant, located in Pangalengan, Bandung regency, West Java with an installed capacity of 227 MWe has two units to generate electricity and deliver to the Jawa, Madura, and Bali grid. The steam extracted from the reservoir contains non-condensable gas of about 1-1.2% of total steam extracted, with the gas composition is CO2 92%, H2S 2%, NH3 0.1%, and residual gasses 4.9%. Possibilities study of a non-condensable gas exhaust through the condensate injection pipe was created as the efforts in the environmental conservation aspect for reducing carbon released to the atmosphere and reinjected back into the reservoir. This study was simulated in Wayang Windu Unit 2 by calculating the non-condensable gas flow rate from the gas removal system into the condensate injection pipe near of cooling tower blowdown power station area. The analysis result of this study indicates that the non-condensable gas requires a higher flow rate of condensate to dissolve the entire non-condensable gas, and may cause the slug flow pattern which would endanger the condensate pipeline system also destabilize the non-condensable gas exhaust operation process from the condenser through the gas removal system. To deal with this problem, the possibility of exhausting the non-condensable gas produced by the gas removal system can be alternated by flowing its non-condensable gas into a flash absorber system and converting its non-condensable gas into other eco-friendly products and power plant safe.

Health Assessment Method of Equipment in Distribution Court Based on Big Data Analysis in the Framework of Distribution Network of Things

Focusing on the problem that the quantity of equipment in the distribution court is huge and the operation status is difficult to reliably control, a method of equipment health status assessment in the distribution court based on big data analysis in the distribution network of things architecture is proposed. Firstly, based on the internet of things for power distribution, the evaluation system of equipment status in the distribution court is designed to ensure the efficient analysis of massive data through the cooperation of cloud center and edge computing. Then, at the edge of the system, the grey correlation analysis algorithm and the Granger hypothesis method are used to obtain the correlation and causality of the failure rate of equipment components and the influencing factors so as to understand the accurate failure rate of equipment components. Finally, the weight of factors affecting the equipment failure rate is identified by using the dynamic variable weight analytic hierarchy process, and it is corrected in the cloud center; and the overall health degree of the equipment in the distribution court is obtained through transformation. Based on the selected station area model, the proposed method is experimentally demonstrated. The results show that it can accurately obtain the real-time health status of the court equipment and the evaluation accuracy is close to 98%, which provides theoretical support for the operation and maintenance of the distribution network.