This work integrates a multi-objective evolutionary algorithm with the multi-agent transport simulator MATSim and the comprehensive modal emission model simulator CMEM to analyze the evolutionary opti- mization of traffic signals minimizing travel time and fuel consumption on a real-world large scenario. We simulate the movement of 20.000 vehicles on the transport network of a 5×8Km area of Quito including 70 sig- nal lights. Our aim is to clarify the nature and the extent of the conflict between these objectives. We also compare with a single-objective opti- mization algorithm where only travel time is optimized and evaluate the impact of the signals settings on gas emissions.