• Adsorption of nano-iron oxide on arsenic diminishes with increasing humic acid, pH, and iron oxide. • Increasing ionic strength has an inhibitory effect on the arsenic migration. • The fractal model can accurately capture the arsenic migration in porous media. Nanoparticles have been applied to remediate heavy metal pollutants (e.g., arsenic) in groundwater and soil, where the migration mechanism of pollutants in this multi-component system has not been fully understood. To better understand how nano-iron oxide affects arsenic migration under multivariate influence, this study prepared arsenic loaded composite colloids using arsenic (As(V)), humic acid, and nano iron oxide (n-α-Fe 2 O 3 ). Then we explored the migration behavior of the composite colloids (HA-n-α-Fe 2 O 3 ) loaded As(V) in a quartz sand column affected by n-α-Fe 2 O 3 under various humic acid concentrations, pH values, ionic strengths, and ferric oxide contents. Two migration models, including a classical advection-dispersion equation (ADE) and a Hausdorff fractal advection-dispersion equation (HADE), were used to quantify the observed co-migration of arsenic conveyed by HA-n-α-Fe 2 O 3 colloids loaded As(V) in the column. Our analysis indicates that the adsorption capability of nano-iron oxide on arsenic decreases with pH, humic acid and iron oxide concentrations, thus accelerating arsenic movement. While, the increasement of ionic strength enhances the adsorption force of nano-iron oxide on arsenic and suppresses arsenic migration. Furthermore, simulation results suggest that the HADE model outperforms the traditional ADE model in characterizing arsenic migration, where the time derivative index is an indicator of anomalous diffusion.