Urban net CO₂ fluxes measured by eddy covariance (EC) cannot be treated as anthropogenic emissions without biogenic constraints, because they integrate fossil-fuel sources, biogenic processes, human respiration, and changing footprints. Existing partitioning approaches often require isotopes, tracers, multi-species fluxes, or clean vegetation/emission sectors unavailable at many urban sites. We developed a footprint-informed ecological parameter-migration framework to constrain anthropogenic CO₂ fluxes (F_ff) in mixed urban source areas of Guangzhou, a humid subtropical megacity. A highly vegetated, weakly disturbed suburban donor site provided ecological parameters, which were transferred to a mixed urban target site using dynamic footprints and footprint-weighted enhanced vegetation index (EVI_fp). The migrated parameters produced plausible diurnal and seasonal gross primary productivity (GPP) and ecosystem respiration (R_eco), supporting the donor–target constraint. At the target site, daytime biogenic uptake masked anthropogenic emissions and occasionally drove net CO₂ flux toward neutral or weakly negative values. After subtracting R_eco, GPP, and human respiration, F_ff remained consistently positive throughout the day (1.80–5.14 μmol m^−2 s^−1). F_ffshowed morning and evening peaks consistent with NO_x, CO, wind-sector source areas, and traffic indicators, while footprint-aligned inventories provided magnitude context and suggested spatial-proxy mismatch in a high-population urban functional zone with relatively low on-site combustion. Uncertainty was dominated by GPP light-response structure, with smaller effects from other perturbations. These results demonstrate the feasibility of extracting footprint-scale F_ff from mixed urban source areas using conventional EC, remote-sensing, and footprint data where isotopic or multi-species flux observations are unavailable.