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The Surface Urban Energy and Water Balance Scheme (SUEWS) has recently been introduced to include a bottomup approach to modelling carbon dioxide (CO2) emissions and sink in urban areas. In this study, SUEWS is evaluated against radiation flux observations and eddy covariance (EC) measured turbulent fluxes of sensible heat (QH), latent heat (QE), and CO2 (FC) at a densely built neighborhood in Beijing. The model sensitivity to maximum conductance (gmax) and leaf area index (LAI) is examined. Site-specific gmax is obtained from observations over local vegetation species, and LAI parameters by optimization with remotely sensed LAI obtained from a MODIS/Terra data product. For simulation of anthropogenic CO2 components, local traffic and population data are collected. In model evaluation, the mismatch between the measurement source area and simulation domain is also considered. Using the optimized gmax and LAI, the modelling of heat fluxes is noticeably improved, showing higher correlation with observations, lower bias, and more realistic seasonal dynamics of QE and QH. In comparison to heat fluxes, the FC module shows lower sensitivity to the choice of gmax and LAI. This can be explained by the low relative contribution of vegetation to net FC in the modelled area. SUEWS successfully reproduces the average diurnal cycle of FC and annual cumulative sums. Depending on the size of the simulation domain, the modelled annual accumulated FC ranges from 7.2 to 8.5 kg C m-2 yr-1, when compared to 7.5 kg C m-2 yr-1 observed by EC. Traffic is the dominant CO2 source, contributing 63-73% to the annual total CO2 emissions, followed by human metabolism (14-18%), respiration released by vegetation and soil (6-11%) and building heating (6-9%). Vegetation photosynthesis offsets only 4-8% of the total CO2 emissions. We highlight the importance of choosing optimal LAI parameters and gmax when SUEWS is used to model surface fluxes. The FC module of SUEWS is a promising tool in quantifying urban CO2 emissions at the local scale, and therefore assisting to mitigate urban CO2 emissions. [ABSTRACT FROM AUTHOR]