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.
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Acknowledgments
The article was supported by the Fundamental Research Funds for the Central Universities (No. FRF-SD-12-013A). The authors deeply appreciate the anonymous reviewers for their insightful comments and suggestions, which greatly contributed much to improving the manuscript.
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Liu, F., Wen, Z. & Zheng, L.J. Mathematical modeling for air quality management under stochastic and interval uncertainties. Stoch Environ Res Risk Assess 29, 1485–1498 (2015). https://doi.org/10.1007/s00477-014-0934-z
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DOI: https://doi.org/10.1007/s00477-014-0934-z