A process-based biogeochemistry model, DNDC-Rice, was modified to simulate rice growth and CH 4 emission under elevated atmospheric CO 2 concentration, [CO 2 ]. It simulates the effect of [CO 2 ] on the photosynthetic rate by an empirical parameter (β-factor), which is calibrated based on observed biomass under varied [CO 2 ]. Rice growth is linked to CH 4 emission through rhizodeposition of C and the rice plant's conductance of CH 4 , which depend on the root biomass and tiller density, respectively. DNDC-Rice was tested using five years of rice growth data and four years of CH 4 emission data from a free-air CO 2 enrichment (FACE) experiment in a Japanese rice field, in which [CO 2 ] was controlled at 200 ppm above ambient.In the experiment, FACE increased the average final aboveground biomass by 11% and seasonal CH 4 emission by 22%. By calibrating the β-factor of photosynthesis calculation, DNDC-Rice successfully predicted the final aboveground biomass across the years and the [CO 2 ] treatments. However, it underestimated the enhancement of CH 4 emission by FACE, to be only 9% as the average over the four years. We found this discrepancy to be attributed to the modeling of photosynthesis, root growth and exudation, and rice tiller conductance of CH 4 under elevated [CO 2 ]. These results indicate that DNDC-Rice needs to be further refined using detailed data on these plant processes in order to simulate future CH 4 emission under elevated [CO 2 ].