This paper addresses the residential load scheduling problem with the objective of investigating the influence of price and CO₂ signals in (i) the electricity bill, (ii) the consumer inconvenience, (iii) the electric peak load, and (iv) the CO₂ emissions. These objectives were considered widely in the literature; however, they were not considered simultaneously in one model before. Furthermore, CO₂ emissions targets constraint was not considered in the previous literature. This paper contributes by twofold. First, the CO₂ signal is drawn up based on the proposed generation-mix plan in South Africa and an hourly CO₂ emissions limit is guaranteed. Second, a multi-objective mixed integer programming model is proposed, and a preemptive multi-objective optimization approach is applied. The model is tested with and without considering the hourly CO₂ emissions limit. Furthermore, the model is solved at four scenarios to explore the effect of the price and CO₂ signals and the order of optimization. Results showed that the price and CO₂ signals and the order of optimization have remarkable effect on the appliance schedule and on the four objectives.