Industrialization and population growth have led to a significant expansion of human activities, causing a substantial increase in greenhouse gas emissions and giving rise to a series of urgent environmental issues. Cities are the primary contributors to carbon emissions in China, and urban households constituting a major source. Therefore, studying the carbon emissions from urban households is crucial for energy conservation and emission reduction. Existing research in China often overlooks the carbon emission differences in lifestyle choices at the urban household scale in small and medium-sized cities. This paper focuses on the carbon emissions resulting from the everyday and diverse transportation and diet choices among urban households in the Bincheng District. The study employs methods such as the carbon emission coefficient approach, multiple stepwise regression, and ordinal logistic regression to investigate carbon emissions and their mechanisms. The results show that the average carbon emissions from transportation and diet patterns in urban households in the study area are approximately 357.97 kgCO₂/month, with a proportional relationship of about 4:1 between transportation and diet emissions. Private cars, ride-hailing services, motorcycles, buses, and electric bikes contribute 92.72%, 4.88%, 1.83%, 0.37%, and 0.19%, respectively, to transportation-related carbon emissions. Home dining, eating out, and takeaway contribute 75.29%, 19.71%, and 5% to dietary carbon emissions, respectively. The analysis reveals that the education level of the household head, family income, and household size are three influencing factors significantly impacting household transportation and diet carbon emissions. All factors show a positive correlation with carbon emissions. These factors influence carbon emissions by affecting household choices. The analysis further discovers that the education level of the household head influences the purchase of private cars and the frequency of dining out and ordering takeout. Family income affects the frequency of using ride-hailing services, while household size primarily influences per capita values of transportation and dietary activities. The paper concludes with some recommendations for carbon reduction, offering valuable insights for the implementation of urban ecological sustainability and nationwide low-carbon initiatives.