© 2018 by the authors. In this study, an optimized industry-environment model is proposed for identifying environmental risk under uncertainties. The strategy associated with an emission-permit trading mechanism has been introduced into the industrial-environment regulation (model) for remitting the pressures of frequent/severe haze events in Beijing City. A dual stochastic mixed fuzzy risk analysis method with Laplace's criterion (DSFRL) can be embedded into industry-environment issues with a trading emission-permit trading mechanism (IEST) for handling uncertainties regarded as possibility and probability distributions. Meanwhile, this can also reflect the environmental risks and corresponding system benefits due to the occurrence of a random event (such as random wind velocity). Based on the application of the proposed IEST with DSFRL, the numbers of the obtained results associated with production reduction, adjustment of industrial layout pattern, emission-permit transactions, pollutant mitigation and system benefits under various Laplace criterion cases can be analyzed. A tradeoff between production development and pollution mitigation based on the preference of policymakers can be used for rectifying current strategies with a sustainable mode, which can prompt an effort to confront air pollution.