Mathematical modeling for air quality management under stochastic and interval uncertainties

Abstract

In this study, an inexact stochastic robust air quality management model (ISRAQMM) was developed for supporting regional air pollution control. The Fengrun district in Tangshan City, China, was used as a study case for demonstration. The ISRAQMM has the advantages of reflecting uncertainty and evaluating trade-offs between system economy and reliability, where the model parameters are provided as discrete intervals and deterministic values under various scenarios. The model's objective function was an integration of the expected cost, cost variability and penalty function of constraints violation rather than the traditional objective function considering only the economic factor; meanwhile, the inexact model parameters were expressed as discrete intervals, which have low data requirements. A variety of solutions were obtained, which could be used to help evaluate the trade-off between system economy and reliability. Using the case study, the applicability of the ISRAQMM was demonstrated. A set of conservative solutions with lower risks and cost-effective solutions with higher risks was provided. The balanced scenario solution was recommended for decision makers, since it respects both system economy and reliability. The successful applications of the ISRAQMM in the studied real world are expected to be a good demonstration for many other areas.

Economic and Flexible Design under Uncertainty for Steam Power Systems Based on Interval Two-Stage Stochastic Programming

“…In recent years, considering that the single uncertain optimization method has its applicable conditions and advantages and disadvantages in solving practical problems so that it cannot deal with complex uncertain systems, the coupling of uncertain optimization methods to solve complex uncertain problems was successfully applied in many fields, such as water resource management, − waste management, − water quality management, , end-of-life vehicle management, , air quality management, − energy system management, , and so on. The coupling of uncertain optimization methods not only integrates the advantages of these methods but also can achieve a certain degree of complementary among their limitations.…”

DCT-based Least-Squares Predictive Model for Hourly AQI Fluctuation Forecasting

“…Benis et al (2013) designed one multi-objective and multi-pollutant sensitive AQMN ("air quality monitoring net work") using an integrated optimization approach. For the regional air pollution management and control, Liu et al (2015) presented a called ISRAQM ("inexact stochastic robust air quality management") model. We see that the AQI, which is an index for describing air quality and easy for the public to understand, has been one of daily concerns of the general public.…”