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Management of Occupational Exposure to Engineered Nanoparticles Through a Chance-Constrained Nonlinear Programming Approach

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  • Zhi Chen

    (Department of Building, Civil, and Environmental Engineering, Concordia University, Montreal, QC H3G 1M8, Canada
    Key Laboratory of Industrial Ecology and Environmental Engineering (MOE), School of Environmental Science and Technology, Dalian University of Technology, Dalian 116024, China)

  • Yuan Yuan

    (Department of Building, Civil, and Environmental Engineering, Concordia University, Montreal, QC H3G 1M8, Canada)

  • Shu-Shen Zhang

    (Key Laboratory of Industrial Ecology and Environmental Engineering (MOE), School of Environmental Science and Technology, Dalian University of Technology, Dalian 116024, China)

  • Yu Chen

    (Key Laboratory of Industrial Ecology and Environmental Engineering (MOE), School of Environmental Science and Technology, Dalian University of Technology, Dalian 116024, China)

  • Feng-Lin Yang

    (Key Laboratory of Industrial Ecology and Environmental Engineering (MOE), School of Environmental Science and Technology, Dalian University of Technology, Dalian 116024, China)

Abstract

Critical environmental and human health concerns are associated with the rapidly growing fields of nanotechnology and manufactured nanomaterials (MNMs). The main risk arises from occupational exposure via chronic inhalation of nanoparticles. This research presents a chance-constrained nonlinear programming (CCNLP) optimization approach, which is developed to maximize the nanaomaterial production and minimize the risks of workplace exposure to MNMs. The CCNLP method integrates nonlinear programming (NLP) and chance-constrained programming (CCP), and handles uncertainties associated with both the nanomaterial production and workplace exposure control. The CCNLP method was examined through a single-walled carbon nanotube (SWNT) manufacturing process. The study results provide optimal production strategies and alternatives. It reveal that a high control measure guarantees that environmental health and safety (EHS) standards regulations are met, while a lower control level leads to increased risk of violating EHS regulations. The CCNLP optimization approach is a decision support tool for the optimization of the increasing MNMS manufacturing with workplace safety constraints under uncertainties.

Suggested Citation

  • Zhi Chen & Yuan Yuan & Shu-Shen Zhang & Yu Chen & Feng-Lin Yang, 2013. "Management of Occupational Exposure to Engineered Nanoparticles Through a Chance-Constrained Nonlinear Programming Approach," IJERPH, MDPI, vol. 10(4), pages 1-19, March.
    • Handle: RePEc:gam:jijerp:v:10:y:2013:i:4:p:1231-1249:d:24547
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    References listed on IDEAS

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