whether in the air or aqueous phase, would be more likely drawn to the interface in the classical model than in the NNP model. In contrast, the PMF analysis shows that CO 2 move more easily between the two phases in the classical model due to lower energy barriers, as compared to the NNP model. The opposite trends between the electrostatic potential profile and PMF data indicate that, while electrostatic potential based on fixed point charges reveals local electric fields and potential wells at the interface, it does not fully capture the free energy landscape governing molecular transport. The latter includes electrostatic contributions from induced charges and polarization together with the thermally induced sur-face fluctuations, and solvent effects from asymmetric interactions with interfacial water molecules. To get more details into the solvent effects, we computed the radial distribution function (RDF) between the carbon atom of CO 2 (C CO2 ) and the oxygen atom of water (O H2O ) at the interface using instantaneous interface definitions. Likewise PMFs on Figure , the RDFs (Figure ) show stronger interactions between CO 2 and water in the NNP model compared to the classical model, pointing to differences in the solvent effects controlling CO 2 transport across the liquid phase boundary. In the classical model, the weaker total solvation effects at the interface results in CO 2 moving back and forth between the interface and either the air or bulk aqueous phase, decreasing its residence time in the truly interfacial layer and speeding up its dynamics at the interface. To investigate this behavior further, we computed the survival probability of CO 2 in the interfacial layer. Specifically, we calculated the probability of finding CO 2 at a later time t, given its presence in the instantaneous layer at t = 0 (Figure ). The results showed that the survival probability decayed more rapidly in the classical model compared to the NNP model, indicating faster dynamics of CO 2 at the air-water interface when modeled with classical potentials. Similarly, faster dynamics of H 2 O was observed in the classical system compared to the NNP system (Figure ). Moreover, we observed significant differences in the spread of the PMF and electrostatic potential (due to wider charge density distribution, Figure ), which we attribute to variations in the surface fluctuations at the interfaces modeled using classical and NNP potentials. To quantify the extent of these surface fluctuations, we employed a method similar to that described in ref. . First, we computed the density profiles of water and CO 2 in the instantaneous layers (Figure ). These density profiles were fitted to the Gaussian distribution function and the standard deviation σ is used to compute the Full Width at Half Maximum (FWHM) as 2 2 ln(2) σ, which is used to characterize the spread of the surface fluctuations (Figure ). The FWHM was calculated to be 2.94 Å for the classical model and 3.07 Å for the NNP model, indicating that water is more widely spread at the interface in the NNP model. This wider spread of interface leads to larger surface fluctuations compared to the classical model, possibly contributing to the free energy associated with the CO 2 transport from air to the aqueous phase. As a result, significant differences in the charge distribution (Figure ) and orientation of water at the interface were observed between the two models (Figure ). Specifically, in the NNP model, water molecules demonstrate a more pronounced spread of water tilted toward the air phase (with similar maximum cos values) within the interfacial region (the overall water orientation behavior is consistent with previously observed DFT-MD results ) compared to the classical model. This pronounced tilt-where the hydrogen atoms of H 2 O are more oriented (thicker water layer showing tilt in the NNP model compared to classical water model) toward the air-along with slower water dynamics (as shown by the water O-H vector orientation in Figure ), creates favorable configurations for stronger interactions between water and CO 2 . Consequently, the free energy barrier for CO 2 transport from the interface into the aqueous phase rises, driven by the combined effects of enhanced surface fluctuation-induced capillary waves, extended molecular orientation, and improved solvation. In summary, we studied the structure and dynamics of CO 2 at the air-water interface using machine learning simulations and compared the results with classical forcefields simulations. Our findings reveal significant differences in the distribution, dynamics, and free energy associated with CO 2 transport to the aqueous phase. Specifically, we observed that the classical force fields underestimated the free energy barrier for CO 2 transport and exhibited weaker interactions between CO 2 and H 2 O at the air-water interface compared to neural network potentials. First-principles accuracy is essential for computing CO 2 thermodynamics and kinetics at evolving interfaces, as these simulations inherently include explicit polarization effects necessary for accurately describing interfacial chemical and transport processes. Despite stronger interfacial electrostatic potential from a fixed point-charge model, CO 2 interacts weaker with classical water. These weaker interactions resulted in faster adsorption and desorption kinetics at the air-water interface. We observed enhanced surface fluctuations and interface broadening for the NNP compared to the classical model. The contributions from the thermal surface fluctuations and solvent rearrangements are often overlooked but are essential for accurately characterizing chemical reactions and transport processes at the interface, and should be considered when using computational methods to model interfacial chemical reactions and transport properties.