Among the CO2 emission reduction programs, cap-and-trade (C&T) is one of the most used policies. Economic studies have shown that C&T policies for electricity networks, while reducing emissions, will likely increase price and decrease consumption of electricity. This paper presents a two layer mathematical-statistical model to develop Pareto optimal designs for CO2 cap-and-trade policies. The bottom layer finds, for a given C&T policy, equilibrium bidding strategies of the competing generators while maximizing social welfare via a DC optimal power flow (DC-OPF) model. We refer to this layer as policy evaluation. The top layer (called policy optimization) involves design of Pareto optimal C&T policies over a planning horizon. The performance measures that are considered for the purpose of design are social welfare and the corresponding system marginal price (MP), CO2 emissions, and electricity consumption level. (C) 2014 Elsevier Ltd. All rights reserved.