Promoting active travel behavior and decreasing transport-related carbon dioxide （CO2） emissions have become a priority in many Chinese cities experiencing rapid urban sprawl and greater automobile dependence. Howev...Promoting active travel behavior and decreasing transport-related carbon dioxide （CO2） emissions have become a priority in many Chinese cities experiencing rapid urban sprawl and greater automobile dependence. However, there are few studies that holistically examine the physical and social factors associated with travel CO2 emissions. Using a survey of 1525 shoppers conducted in Shenyang, China, this study estimated shopping-related travel CO2 emissions and examined how the built environment and individual socioeconomic characteristics contribute to shopping travel behavior and associated C02 emissions. We found that, firstly, private car trips generate nearly eight times more carbon emissions than shopping trips using public transport, on average. Second, there was sig- nificant spatial autocorrelation with CO2 emissions per trip, and the highest carbon emissions were clustered in the inner suburbs and between the first and second circumferential roads. Third, shopping travel CO2 emissions per trip were negatively correlated with sev- eral built environment features including population density, the quantity of public transport stations, road density, and shop density. They were also found to be significantly related to the individual socio-eeonomic characteristics of car ownership, employment status, and education level using a multinomial logistic regression model. These empirical findings have important policy implications, assisting in the development of measures that contribute to the sustainability of urban transportation and meet carbon mitigation targets.展开更多
Due to the importance of the social environment impact of highway construction project, an advanced evaluation is required to incorporate situations such as uncertainty, incompatibility and less information. This pape...Due to the importance of the social environment impact of highway construction project, an advanced evaluation is required to incorporate situations such as uncertainty, incompatibility and less information. This paper proposes a gray matter-element evaluation model based on the information entropy. The model is developed by combining both quantitative and qualitative methods, using probability theory to convert quantitative index to qualitative index, and the weight of those indexes were determined through synthesised integral weighting method, integrating matter-element theory, grey theory, and information theory. The model is then applied to evaluate the impact of the social environmental impact of highway construction project which will provide support for decision makers. Cheng-Yu highway and Shen-Da highway were selected for model application, and good results were achieved similar to the real situation.展开更多
基金Under the auspices of National Natural Science Foundation of China(No.41201159,41571152,41401478,41201160,41001076)the Key Research Program of the Chinese Academy of Sciences(No.KSZD-EW-Z-021-03,KZZD-EW-06-03)
文摘Promoting active travel behavior and decreasing transport-related carbon dioxide （CO2） emissions have become a priority in many Chinese cities experiencing rapid urban sprawl and greater automobile dependence. However, there are few studies that holistically examine the physical and social factors associated with travel CO2 emissions. Using a survey of 1525 shoppers conducted in Shenyang, China, this study estimated shopping-related travel CO2 emissions and examined how the built environment and individual socioeconomic characteristics contribute to shopping travel behavior and associated C02 emissions. We found that, firstly, private car trips generate nearly eight times more carbon emissions than shopping trips using public transport, on average. Second, there was sig- nificant spatial autocorrelation with CO2 emissions per trip, and the highest carbon emissions were clustered in the inner suburbs and between the first and second circumferential roads. Third, shopping travel CO2 emissions per trip were negatively correlated with sev- eral built environment features including population density, the quantity of public transport stations, road density, and shop density. They were also found to be significantly related to the individual socio-eeonomic characteristics of car ownership, employment status, and education level using a multinomial logistic regression model. These empirical findings have important policy implications, assisting in the development of measures that contribute to the sustainability of urban transportation and meet carbon mitigation targets.
文摘Due to the importance of the social environment impact of highway construction project, an advanced evaluation is required to incorporate situations such as uncertainty, incompatibility and less information. This paper proposes a gray matter-element evaluation model based on the information entropy. The model is developed by combining both quantitative and qualitative methods, using probability theory to convert quantitative index to qualitative index, and the weight of those indexes were determined through synthesised integral weighting method, integrating matter-element theory, grey theory, and information theory. The model is then applied to evaluate the impact of the social environmental impact of highway construction project which will provide support for decision makers. Cheng-Yu highway and Shen-Da highway were selected for model application, and good results were achieved similar to the real situation.
