2023 Vol.6
Low Carbon Transportation & Built Environment
Review on Optimization Methods of Green Transportation System in Urban Built Environment
Abstract: Urban green transportation system is a multi-level complex system including rail transportation, bus transportation, shared bicycles, and walkways. It has multiple characteristics such as practicality, convenience, economy and sustainability, which is of great significance to the current low-carbon and energy-saving built environment of the city. At present, scholars in related fields at home and abroad have studied the optimization of green transportation systems from multiple perspectives, and formed analysis and optimization methods for some specific problems. Taking the supply and demand relationship as the basic clue, the article attributes the optimization of urban green transportation systems to four main aspects, namely, traffic carrying capacity, traffic demand, coupling analysis, and multi-objective optimization, and summarizes the results achieved by the relevant research and practice. The article evaluates the problems of existing research from both macro and micro perspectives, and points out the development trend of future research. Finally, the article synthesizes the characteristics and advantages of each technique and proposes a framework for optimizing green transportation systems in urban built environment based on supply and demand.
Study on the Impact of Urban Built Environment on Commuting Carbon Emissions: A Case Study of Beijing
Abstract: This article is based on the theory of urban form and the theory of spatial relationships between work and residence. Based on questionnaire data and qualitative interview data, stratified regression research and qualitative research methods are used to investigate the impact of built environment on commuting behaviors. Three representative areas in Beijing, namely Dashilan Community, Caochang Community, and Tiantongyuan Community located on the outskirts of Hutong in the old urban area and the central urban area, are conducted on-site research interviews. Research has found that: (1) Beijing's commuting carbon emissions exhibit spatial distribution characteristics of low carbon in the center and high carbon in the periphery. (2) Public transportation supply and rail transit have a significant impact on reducing commuting carbon emissions. Streets with relatively balanced work and housing, as well as streets with a high density of rail and bus networks, have relatively low carbon emissions from commuting. (3) Not only will the built environment characteristics of the residence affect commuting carbon emissions, but the demand for additional activities during commuting and the ease of transfer also have an indirect impact on commuting carbon emissions. Therefore, the impact of built environment on commuting carbon emissions includes not only direct material and spatial factors, but also indirect individual perspectives. Research can provide references for developing carbon reduction strategies tailored to local conditions in large cities.
Study on the Characteristics of Travel and Job-housing Balance in Urban Key Functional Areas: A Case Study of Beijing
Abstract: The issue of job-housing separation has become increasingly critical in large cities. This study takes Beijing as a case study and employs big data analysis to investigate the characteristics of travel patterns and job-housing balance in key urban functional areas. Firstly, mobile signaling data is utilized to extract user origin-destination (OD) information, allowing for the analysis of travel characteristics such as time, distance, and time consumption in each functional area. Subsequently, a house/job location identification algorithm is applied to determine users' residential and workplace locations, and the independence index is introduced to measure the degree of job/housing separation. The findings reveal that job-housing separation exceeds 50% in each functional area. By comparing the density of urban infrastructure supporting facilities and the travel characteristics of functional areas using Point of Interest (POI) data, we identify the Huilongguan area as having fewer transportation-supporting facilities, leading to longer commuting distances and time consumption. Finally, specific suggestions are provided to improve the urban spatial structure and facility configuration, in order to better cater to people's commuting needs. This study offers valuable insights for urban planners and policymakers to address the job-housing balance issue in key functional areas and enhance urban mobility.
The Carbon Emission Mechanism of Traffic Congestion in Mega Cities Caused by Job-housing Imbalance: A Case Study of Commuting Behavior from Suburban Housing to Urban Workplaces in Tianjin
Abstract: Using multiple data such as OD data, Baidu Map real-time congestion data and POI data, typical commuting behavior routes from suburban housing to urban workplaces in Tianjin during morning and evening peak hours are proposed with kernel density analysis method. Furthermore, regression analysis is used to analyze the characteristics and influencing factors of total carbon emissions from congestion. The research results show that the typical commute routes are mainly concentrated between large residential areas in the suburbs and the workplaces in the adjacent central urban area. There are differences in the characteristics and formation mechanisms of carbon emissions from morning and evening peak congestion. Land use, transportation organization, and public transportation facilities around suburban residential spaces have a differentiated impact on congestion carbon emissions during morning and evening peak hours. Increasing the density of the road network and reducing the distance between public transportation stations can effectively reduce the carbon emissions caused by congestion.
Comparison of Regional Transport Integration Characteristics and Development Strategies of China and Japan from Low-carbon Perspective: A Case Study of Guangdong-Hong Kong-Macao Greater Bay Area and Tokyo Bay Area
Abstract: As an important part of the low-carbon economy, low-carbon transportation is a new development goal and requirement for the transportation system in the face of the global energy crisis and environmental degradation. Regional transportation integration is a sustainable development mode to realize the optimal benefit of bay areas. It is of great significance to study its development characteristics and strategies to promote the efficient allocation of resources and the free flow of elements. In this paper, the comparative study of Chinese and foreign cities is taken as the main research idea, and the CUTE matrix is used as the research method. From the aspects of technical tools, control tools, information tools and economic tools, this paper makes a comparative study on the integration of low-carbon regional transportation in the Guangdong-Hong Kong-Macao Greater Bay Area and the Tokyo Bay Area. The comparison results show that the Guangdong-Hong Kong-Macao Greater Bay Area has a significant gap with the Tokyo Bay Area in land use mixing, rail transit development and public awareness. The stock characteristics of traffic development in the Tokyo Bay Area are obvious, and the Guangdong-Hong Kong-Macao Greater Bay Area still shows incremental development characteristics. The purpose of this study is to compare and summarize the low-carbon experience and challenges of regional transportation integration in the bay areas of China and Japan, and to provide references for the development of transportation integration in the Guangdong-Hong Kong-Macao Greater Bay Area in the process of China's ecological civilization system reform, so as to promote the development of low-carbon transportation in global urban agglomerations.
Impact of Built Environment of Urban Rail Transit Stations on Metro Passenger Flow: A Case Study of Shenzhen
Abstract: Traditional linear models cannot display the nonlinear results of indicators, making it difficult to reflect the relative importance and impact threshold of each indicator. This study uses Shenzhen rail transit smart card date to construct a gradient boosting decision tree (GBDT) model to explore the non-linear relationship between the built environment and passenger flow in different time periods, hoping to provide references for transportation planning, station development, and optimization of built environment around stations in cities, especially mega cities. The results show that: ① Different built environments have different relative importance to passenger flow in different time periods. Building floor area ratio, proportion of residential land, proportion of commercial land, and distance from CBD all have relatively high and robust effects on site passenger flow. ② There is a significant nonlinear relationship and threshold between the built environment and passenger flow. ③ When the land use mixing degree is above 0.60 and the distance from CBD exceeds 17 km, the daily passenger flow shows a significant downward trend. ④ The impact mechanism of the built environment on the passenger flow in different time periods is not completely the same. ⑤ The promotion effect of urban villages on subway passenger flow is very significant.
Beijing Metropolitan Area Spatial Boundary Identification and Commuting Rate Characteristics Based on Spatial Merge Techniques
Abstract: Under the background of Beijing-Tianjin-Hebei regional integration, this paper uses mobile phone signaling data to study the spatial characteristics of commuting with the city center as the focus, to identify the spatial boundary and expansion trend of the Beijing metropolitan area. This paper aims to provide policy references for the integration of the comprehensive transport network of the urban agglomeration and metropolitan area under the background of Beijing-Tianjin-Hebei integration, and for the public transport service that provides high-quality commuting services. GIS-based spatial fusion analysis technology is adopted to effectively identify mobile phone users' places of residence, employment, and commuting OD chains, and the spatial characteristics of the metropolitan area's commuting range are determined by measuring the commuting rate from the peripheral areas to the center. The analysis shows that the spatial level of the metropolitan area is correlated with the commuting rate. Taking the central city of Beijing as the center of commuting, the 30% commuting rate contour of the first circle corresponds to the area within 30 km, which is the most active and intensive zone of urban commuting behaviors. The 10% commuting rate contour of the second circle corresponds to an irregular circle of 30 km-50 km, which is about the boundary of the metropolitan area. The outermost 5% commuting rate contour corresponds to a zone of occasional commuting beyond 50 km, which shows a discontinuity in spatial distribution.