Promoting active travel behavior and decreasing transport-related carbon dioxide(CO_2) 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 CO_2 emissions. Using a survey of 1525 shoppers conducted in Shenyang, China, this study estimated shopping-related travel CO_2 emissions and examined how the built environment and individual socioeconomic characteristics contribute to shopping travel behavior and associated CO_2 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 significant spatial autocorrelation with CO_2 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 CO_2 emissions per trip were negatively correlated with several 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-economic 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. Promoting active travel behavior and decreasing transport-related carbon dioxide (CO_2) 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 CO_2 Using a survey of 1525 shoppers conducted in Shenyang, China, this study estimated shopping-related travel CO_2 emissions and examined how the built environment and individual socioeconomic characteristics contribute to shopping travel behavior and associated CO_2 emissions. We found that, initially, private car trips generate nearly eight times more carbon emissions than shopping trips using public transport, on average. Second, there was significant spatial autocorrelation with CO_2 emissions per trip, and the highest carbon emissions were clustered in the inner suburbs and between the first and second circumferential Third, shopping travel CO_2 e missions per trip were negatively correlated with several 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-economic characteristics of car ownership, employment status , and education level using a multinomial logistic regression model. These measures were important in the development of measures that contribute to the sustainability of urban transportation and meet carbon mitigation targets.