Abstract: To address the challenges of global climate change and the imperative of urban low-carbon transformation, this study focused on the temporal characteristics and multi-factor coupling effects of community scale carbon emissions. A refined calculation method was proposed and applied to three typical high-density residential areas in Guangzhou. Based on dynamic simulation models for building energy consumption, transportation statistics, and municipal facility accounting frameworks, this study quantifies carbon emissions across buildings, transportation, and municipal services by integrating field survey parameters and carbon emission factors. The results revealed notable temporal variation in building carbon emissions, the residential and commercial buildings displayed higher emissions than other building types, with residential buildings accounting for the largest share of total emissions. Transportation emissions were primarily driven by gasoline-powered vehicles, constituting 76% of total transportation emissions, with private cars being the largest contributor. The wastewater treatment contributed 63% of carbon emissions from water use and the composting had the lowest carbon emission in waste treatment. In urban road lighting carbon emissions, branch road lighting exceeds 50%. Also, the carbon sequestration capacity per unit area of green space is lowest among all types. This study clarifies the impacts of spatial structure, population density, and building types on carbon emissions by accounting the multi-factor carbon emissions in community scale.