Land Surface Models (LSMs) are crucial elements of Earth System Models used to estimate the effects of anthropogenic greenhouse gas (GHG) emissions on Earth's climate. Nevertheless, as well as land use change and direct GHG emissions, anthropogenic activities are also associated with contaminant emissions and depositions. Although contamination has a recognized impact on soil processes such as GHG emissions, soil contamination is currently not considered as an important process to consider into LSMs. In this study we hypothesized that soil contamination has significant impact on soil CO2 emissions such as heterotrophic respiration (Rh). To this end, we analyzed how soil contamination may account for residuals of modeled Rh from 11 LSMs as compared to Rh products derived from observations over Europe. We used generalized least squared mixed models to evaluate the primary factors driving of the model residuals. Among contaminants, we focused on copper (Cu), which is widely used in industry or agriculture, causing significant diffuse contamination. Additionally, research demonstrated a strong correlation between soil Rh and Cu availability to soil fauna and various soil pedological and climatic parameters. Hence, we completed our analysis by including pedo-environmental parameters and by analyzing Rh against a proxy of bioavailable Cu. Our findings indicate that Cu is a non-negligible variable in explaining the Rh models inaccuracy considering either total or free Cu forms. Therefore, it can be concluded that Cu should not be disregarded as a key factor in predicting Rh.