A production-emission nexus based stochastic-fuzzy model for identification of urban industry-environment policy under uncertainty

In this study, a hybrid production-emission nexus based stochastic-fuzzy production planning and air pollution management model (PE-SF-PP) can be proposed for coordinating industrial activities and environmental protection under multiple uncertainties. It can not only handle objective uncertainties expressed as probability and possibility distributions, but also quantify subjective imprecision presented as fuzzy sets with risk-preference attitudes in a production planning and air pollution management issue (PPM). The proposed PE-SF-PP model is applied to a practical PPM in the Beijing city for identifying current urban industry-environment policies. Results of production reduction, industrial layout pattern, production mode, pollutant control measure selection, retreatment efficiency, industrial productivity, and system benefit under various environmental regulation scenarios are analyzed. The obtained results can support policymakers adjusting current strategies with sustainable and robust manner, which can be beneficial to construct a cleaner production mode and optimized industry-environment policy for alleviating urban production-emission conflict.