Nowadays the growing concerns about the environment and society in general led companies to invest in a sustainable development. In this way, companies’ design and planning decisions need to encompass simultaneously economic, environmental and social concerns. In addition, considering the complexity associated with market uncertainties, there is the need to consider risk management. This work is developed along this line and proposes a mixed integer linear programming model (MILP) that accounts for the economic and environmental performances in the same objective function by monetizing environmental impacts and simultaneously considering the most popular risk measures in the literature, CVaR. The goal is to maximize the difference between the expected net present value and the environmental impact while minimizing the associated risk. The augmented ε-constraint method is used to generate a Pareto-optimal curve in order to determine the trade-off between the objective functions. Conclusions can be drawn based on decision makers’ risk profile as well as how monetization can support the decision maker’s decision. A European supply chain case study is explored.