Spatial-temporal Characteristics and Factors Influencing Commuting Activities of Middle-class Residents in Guangzhou City, China

The middle class in metropolitan Chinese cities has become an important social group. With the rapid development of urbanization and constant advancement of suburbanization, the middle class has increasingly come to influence city traffic. Research into middle-class commuting activities thus has practical significance for improving traffic congestion and reducing the commuting burden in metropolitan cities. Based on a dataset formed by 816 completed surveys, this paper analyzes the commuting mode, time and distance of middle-class residents in Guangzhou City using the descriptive statistical method. The results indicate that private cars are the main commuting mode, followed by public transport. Meanwhile, middle-class residents mainly undertake medium-short time and medium-short distance commuting. The study subsequently uses multilevel logistic regression and multiple linear regression models to analyze the factors that influence commuting mode choice, time and distance. The gender, age, number of family cars, housing source and jobs-housing balance are the most important factors influencing commuting mode choice; housing, population density, jobs-housing balance and commuting mode significantly affect commuting time; and transport accessibility, jobs-housing balance and commuting mode are the notable factors affecting commuting distance. Finally, this paper analyzes what is affecting the commuting activities of middle-class residents and determines the differences in commuting activity characteristics and influence factors between middle-class and ordinary residents. Policy suggestions to improve urban planning and urban management are also proposed.

Spatial Mismatch or Not?Evidence from Public Janitors in Xi’an,China

Research on the spatial mismatch experienced by low-income minority residents is US-centric.However,spatial mismatch is not necessarily an appropriate term when considering the situation of low-wage workers in cities of northwestern China where there is higher proximity between jobs and housing and lower levels of residential segregation.This paper empirically examines the jobs-housing spatial relationship for one of the most typical low-wage groups,namely,public janitors,in Xi’an,China.Also,the causes of the jobs-housing spatial relationship are discussed in detail.Individual-level data based on in-depth interviews and questionnaires,as well as the GIS network analysis method,are used to provide baseline analyses of the jobs-housing spatial relationship.Results indicate that there is no jobs-housing spatial mismatch for public janitors in Xi’an.This can be implied from the short commuting distance and time.A basic cause is that most public janitors rent low-cost accommodation in villages-in-the-city,and in old residential quarters,near to their places of work.Other causes lie in off-peak commuting and high sensitivity to commuting distance due to the greater extent of nonmotorized commuting modes.The conclusions,based on a large number of social surveys,are an illuminating analysis of the spatial mismatch issue among low-wage workers in Chinese cities.

Quantifying Changes of Mobile Source Air Pollution in Metropolitan Areas Using Vehicle Emission Model MOVES

Vehicle emissions are one of the major sources of urban air pollution and are also called mobile source emissions. A large amount of gross vehicle emissions is generated by vehicles commuting between residential homes and the workplace. Homebuyers generally prefer to purchase residential houses that are relatively less expensive, albeit at the cost of relatively longer commuting times. Consumers usually consider additional travel time, fuel consumption, and other personally concerned factors, with less apprehension about the extra air pollution possibly generated. In cities with populations between 15,000 and 1,000,000, an increase of one additional minute of average commuting time is associated with a reduction of 1.9 dollars in housing price per square foot （p-value： 0.038）. To account for the generation of additional air pollution, this paper numerically characterizes factors related to air pollutants caused by additional travel time due to housing prices. Air pollutants such as CO, CO2, NO2, NO, NOx and SO2 as well as fuel consumption were estimated by MOVES （motor vehicle emissions simulator）. The results will be a useful reference to generate recommendations for more efficient reduction of mobile source air pollution in metropolitan areas through joint efforts by government, agencies, the public, and industry from multiple fields including environment protection, land use, housing markets, transportation management, and law enforcement.