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Mixed Integer Linear Programming Models for Selecting Ground-Level Ozone Control Strategies

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Abstract

The traditional strategy for ground-level ozone control is to apply emission reductions across the board throughout certain time periods and locations. In this paper, we study various mixed integer linear programming (MILP) models that seek to select targeted control strategies for the Dallas Fort-Worth (DFW) region to reduce emissions, in order to achieve the State Implementation Plan (SIP) requirements with minimum cost. Statistics and optimization methods are used to determine a potential set of cost-effective control strategies for reducing ozone. These targeted control strategies are specified for different types of emission sources in various time periods and locations. Three MILP models, a static model, a sequential model, and a dynamic model, are studied in this research. These different MILP models allow decision makers to study how the targeted control strategies change under different circumstances. Meanwhile, two types of auxiliary variables are considered as supplemental control strategies in the optimization if the current set of control strategies is unable to reduce ozone to comply with the 8-h ozone standard. Results from the different models can provide decision makers with information concerning how the effectiveness of the control strategies varies with daily emission patterns and meteorology.

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Authors and Affiliations

  1. Department of Industrial & Manufacturing Systems Engineering, The University of Texas at Arlington, P.O. box 19017, Arlington, TX, 76019, USA

    Wei-Che Hsu, Jay M. Rosenberger & Victoria C. P. Chen

  2. Providence Engineering & Environmental Group, 1200 Walnut Hill Lane, Suite 1000, Irving, TX, 75038, USA

    Neelesh V. Sule

  3. Department of Civil Engineering, The University of Texas at Arlington, P.O. box 19308, Arlington, TX, 76019, USA

    Melanie L. Sattler

Authors
  1. Wei-Che Hsu
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  2. Jay M. Rosenberger
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  3. Neelesh V. Sule
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  4. Melanie L. Sattler
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  5. Victoria C. P. Chen
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Correspondence to Wei-Che Hsu.

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Hsu, WC., Rosenberger, J.M., Sule, N.V. et al. Mixed Integer Linear Programming Models for Selecting Ground-Level Ozone Control Strategies. Environ Model Assess 19, 503–514 (2014). https://doi.org/10.1007/s10666-014-9408-4

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  • DOI: https://doi.org/10.1007/s10666-014-9408-4

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