Continuous transportation demand growth in recent years has led to many traffic issues in urban areas. Among the most challenging ones are traffic congestion and the associated vehicular emissions. Efficient design of traffic signal control systems can be a promising approach to address these problems. This research develops a real-time signal control system, which optimizes signal timings at an under-saturated isolated intersection by minimizing total vehicular emissions. A combination of previously introduced analytical models based on traffic flow theory has been used. These models are able to estimate time spent per driving mode (i.e., time spent accelerating, decelerating, cruising, and idling) as a function of demand, vehicle arrival times, saturation flow, and signal control parameters. Information on vehicle activity is used along with the Vehicle Specific Power (VSP) model, which estimates emission rates per time spent in each operating mode to obtain total emissions per cycle. For the evaluation of the proposed method, data from two real-world intersections of Mesogion and Katechaki Avenues located in Athens, Greece and University and San Pablo Avenues, in Berkeley, CA has been used. The evaluation has been performed through both deterministic (i.e. under the assumption of perfect information for all inputs) and stochastic (i.e. without having perfect information for some inputs) arrival tests. The results of evaluation tests have shown that the proposed emission-based signal control system reduces emissions compared to traditional vehicle-based signal control system in most cases.