<p>When considering regulatory approaches to control emission or other pollution sources, two common paradigms are command-and-control or cap-and-trade markets. The former approach can lead to higher aggregate abatement costs. By contrast, in the cap-and-trade scheme, the market determines the price of emissions or other pollution, which has been shown to have a number of successful outcomes. In this paper we provide a game theoretic model for a cap-and-trade market wherein natural processes (e.g., weather and hydrology) lead to stochastic pollution generation when coupled with human activity (e.g., land development). The stochasticity for each market participant is modeled via chance constrained optimization where chance constraints relate to reliability-type, probabilistic compliance of pollution regulations. The resulting player optimization problems are convex due to second-order cone deterministic-equivalent reformulations of these chance constraints as well as other convex constraints. The concatenation of each player’s sufficient Karush-Kuhn-Tucker optimality conditions plus market-clearing conditions then leads to a stochastic, mixed complementarity problem. We provide a specific example for water-quality management and apply it to the Anacostia River in the Washington, DC metro area.</p>