Because of the G4M model non-linearity marginal abatement cost curves (MACCs) are sensitive to variation of the model parameters, irrespective of the fact that the same parameter variations are applied in both zero-CO2 price and non-zero-CO2 price runs. Since integrated assessment models in general are complex computer models with non-linearity one may expect all MACCs constructed using such models are sensitive to variation of the model parameters. The MACCs constructed using G4M are much more sensitive to parameter variation at a certain range of CO2 prices, usually low CO2 prices. The MACCs for total biomass CO2 emissions constructed using G4M are most sensitive to variation of corruption coefficient (measuring efficiency of use of abatement costs) and, on the second place, to agriculture land price. Experts applying MACCs for policy analysis must be aware of uncertainty features of the MACCs as the uncertainty can influence the outcome of the analysis.