Interval-Based Air Quality Index Optimization Model for Regional Environmental Management Under Uncertainty

In this study, an interval-based air quality index optimization (IAQO) method was developed for the planning of regional air quality management systems. The developed IAQO method introduced an air quality index (AQI) concept into an interval mathematical programming (IMP) framework to handle uncertainties expressed as interval values in the model's left- and right-hand sides and objective function over a multipollutant environmental management for its capacity of integrated evaluation and health risk analysis with ambient concentrations. A management problem for controlling total air pollutant concentrations was studied to illustrate applicability of the proposed IAQO approach. A number of scenarios based on different ambient air quality management policies were analyzed. Results indicate that reasonable solutions have been generated under different levels of violating AQI risk. They can help decision makers to identify desired alternatives for mitigating air pollution with cost minimization and for providing services for regional air quality management decisions.